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1102.2035
|
Quasi-Cross Lattice Tilings with Applications to Flash Memory
|
cs.IT math.IT
|
We consider lattice tilings of $\R^n$ by a shape we call a
$(\kp,\km,n)$-quasi-cross. Such lattices form perfect error-correcting codes
which correct a single limited-magnitude error with prescribed
maximal-magnitudes of positive error and negative error (the ratio of which is
called the balance ratio). These codes can be used to correct both disturb and
retention errors in flash memories, which are characterized by having limited
magnitudes and different signs.
We construct infinite families of perfect codes for any rational balance
ratio, and provide a specific construction for $(2,1,n)$-quasi-cross lattice
tiling. The constructions are related to group splitting and modular $B_1$
sequences. We also study bounds on the parameters of lattice-tilings by
quasi-crosses, connecting the arm lengths of the quasi-crosses and the
dimension. We also prove constraints on group splitting, a specific case of
which shows that the parameters of the lattice tiling of
$(2,1,n)$-quasi-crosses is the only ones possible.
|
1102.2091
|
The blogosphere as an excitable social medium: Richter's and Omori's Law
in media coverage
|
physics.soc-ph cs.SI
|
We study the dynamics of public media attention by monitoring the content of
online blogs. Social and media events can be traced by the propagation of word
frequencies of related keywords. Media events are classified as exogenous -
where blogging activity is triggered by an external news item - or endogenous
where word frequencies build up within a blogging community without external
influences. We show that word occurrences show statistical similarities to
earthquakes. The size distribution of media events follows a Gutenberg-Richter
law, the dynamics of media attention before and after the media event follows
Omori's law. We present further empirical evidence that for media events of
endogenous origin the overall public reception of the event is correlated with
the behavior of word frequencies at the beginning of the event, and is to a
certain degree predictable. These results may imply that the process of opinion
formation in a human society might be related to effects known from excitable
media.
|
1102.2114
|
Knowledge Management System Design using Extended Gaia
|
cs.MA
|
An efficient Learning resource centre can be achieved with the help of a
network of collaborating, coordinating and communicating software agents.
Agent-oriented techniques represent an exciting new means of analysing,
designing and building complex software systems. The designing of the
interacting agents is done with the help of Gaia, extended for the multiagent
systems. Gaia is a methodology for agent-oriented analysis and design proposed
by M. Wooldridge [9].
|
1102.2122
|
On the covering radius of first order generalized Reed-Muller codes
|
math.NT cs.IT math.IT
|
We generalize to any q a theorem about covering radius of linear codes proved
by Helleseth, Klove and Mykkelvit. Then we determine the covering radius of
first order generalized Reed-Muller codes in second order generalized
Reed-Muller codes. Using these results, we are able to give bounds for the
covering radius of first order generalized Reed-Muller codes. Finaly, using
Magma, we get some improvements for q=3.
|
1102.2125
|
Improving DPLL Solver Performance with Domain-Specific Heuristics: the
ASP Case
|
cs.AI cs.LO
|
In spite of the recent improvements in the performance of the solvers based
on the DPLL procedure, it is still possible for the search algorithm to focus
on the wrong areas of the search space, preventing the solver from returning a
solution in an acceptable amount of time. This prospect is a real concern e.g.
in an industrial setting, where users typically expect consistent performance.
To overcome this problem, we propose a framework that allows learning and using
domain-specific heuristics in solvers based on the DPLL procedure. The learning
is done off-line, on representative instances from the target domain, and the
learned heuristics are then used for choice-point selection. In this paper we
focus on Answer Set Programming (ASP) solvers. In our experiments, the
introduction of domain-specific heuristics improved performance on hard
instances by up to 3 orders of magnitude (and 2 on average), nearly completely
eliminating the cases in which the solver had to be terminated because the wait
for an answer had become unacceptable.
|
1102.2166
|
Social Structure of Facebook Networks
|
cs.SI nlin.AO physics.soc-ph
|
We study the social structure of Facebook "friendship" networks at one
hundred American colleges and universities at a single point in time, and we
examine the roles of user attributes - gender, class year, major, high school,
and residence - at these institutions. We investigate the influence of common
attributes at the dyad level in terms of assortativity coefficients and
regression models. We then examine larger-scale groupings by detecting
communities algorithmically and comparing them to network partitions based on
the user characteristics. We thereby compare the relative importances of
different characteristics at different institutions, finding for example that
common high school is more important to the social organization of large
institutions and that the importance of common major varies significantly
between institutions. Our calculations illustrate how microscopic and
macroscopic perspectives give complementary insights on the social organization
at universities and suggest future studies to investigate such phenomena
further.
|
1102.2174
|
Linear Temporal Logic and Propositional Schemata, Back and Forth
(extended version)
|
cs.LO cs.AI
|
This paper relates the well-known Linear Temporal Logic with the logic of
propositional schemata introduced by the authors. We prove that LTL is
equivalent to a class of schemata in the sense that polynomial-time reductions
exist from one logic to the other. Some consequences about complexity are
given. We report about first experiments and the consequences about possible
improvements in existing implementations are analyzed.
|
1102.2176
|
Joint Distributed Access Point Selection and Power Allocation in
Cognitive Radio Networks
|
cs.IT math.IT
|
Spectrum management has been identified as a crucial step towards enabling
the technology of the cognitive radio network (CRN). Most of the current works
dealing with spectrum management in the CRN focus on a single task of the
problem, e.g., spectrum sensing, spectrum decision, spectrum sharing or
spectrum mobility. In this work, we argue that for certain network
configurations, jointly performing several tasks of the spectrum management
improves the spectrum efficiency. Specifically, we study the uplink resource
management problem in a CRN where there exist multiple cognitive users (CUs)
and access points (APs), with each AP operates on a set of non-overlapping
channels. The CUs, in order to maximize their uplink transmission rates, have
to associate to a suitable AP (spectrum decision), and to share the channels
belong to this AP with other CUs (spectrum sharing). These tasks are clearly
interdependent, and the problem of how they should be carried out efficiently
and distributedly is still open in the literature.
In this work we formulate this joint spectrum decision and spectrum sharing
problem into a non-cooperative game, in which the feasible strategy of a player
contains a discrete variable and a continuous vector. The structure of the game
is hence very different from most non-cooperative spectrum management game
proposed in the literature. We provide characterization of the Nash Equilibrium
(NE) of this game, and present a set of novel algorithms that allow the CUs to
distributively and efficiently select the suitable AP and share the channels
with other CUs. Finally, we study the properties of the proposed algorithms as
well as their performance via extensive simulations.
|
1102.2180
|
Malagasy Dialects and the Peopling of Madagascar
|
cs.CL physics.soc-ph
|
The origin of Malagasy DNA is half African and half Indonesian, nevertheless
the Malagasy language, spoken by the entire population, belongs to the
Austronesian family. The language most closely related to Malagasy is Maanyan
(Greater Barito East group of the Austronesian family), but related languages
are also in Sulawesi, Malaysia and Sumatra. For this reason, and because
Maanyan is spoken by a population which lives along the Barito river in
Kalimantan and which does not possess the necessary skill for long maritime
navigation, the ethnic composition of the Indonesian colonizers is still
unclear.
There is a general consensus that Indonesian sailors reached Madagascar by a
maritime trek, but the time, the path and the landing area of the first
colonization are all disputed. In this research we try to answer these problems
together with other ones, such as the historical configuration of Malagasy
dialects, by types of analysis related to lexicostatistics and glottochronology
which draw upon the automated method recently proposed by the authors
\cite{Serva:2008, Holman:2008, Petroni:2008, Bakker:2009}. The data were
collected by the first author at the beginning of 2010 with the invaluable help
of Joselin\`a Soafara N\'er\'e and consist of Swadesh lists of 200 items for 23
dialects covering all areas of the Island.
|
1102.2203
|
Some applications of quasi-velocities in optimal control
|
math.OC cs.SY math-ph math.MP
|
In this paper we study optimal control problems for nonholonomic systems
defined on Lie algebroids by using quasi-velocities. We consider both
kinematic, i.e. systems whose cost functional depends only on position and
velocities, and dynamic optimal control problems, i.e. systems whose cost
functional depends also on accelerations. The formulation of the problem
directly at the level of Lie algebroids turns out to be the correct framework
to explain in detail similar results appeared recently (Maruskin and Bloch,
2007). We also provide several examples to illustrate our construction.
|
1102.2207
|
Lossless Coding with Generalised Criteria
|
cs.IT math.IT
|
This paper presents prefix codes which minimize various criteria constructed
as a convex combination of maximum codeword length and average codeword length
or maximum redundancy and average redundancy, including a convex combination of
the average of an exponential function of the codeword length and the average
redundancy. This framework encompasses as a special case several criteria
previously investigated in the literature, while relations to universal coding
is discussed. The coding algorithm derived is parametric resulting in
re-adjusting the initial source probabilities via a weighted probability vector
according to a merging rule. The level of desirable merging has implication in
applications where the maximum codeword length is bounded.
|
1102.2216
|
On the Capacity of Memoryless Channels with Synchronization Errors
|
cs.IT math.IT
|
Memoryless channels with synchronization errors as defined by a stochastic
channel matrix allowing for symbol insertions and deletions in addition to
random errors are considered. Such channels are information stable, hence their
Shannon capacity exists. However, computation of the channel capacity is
formidable, and only some upper and lower bounds on the capacity (for some
special cases) exist. In this short paper, using a simple methodology, we prove
that the channel capacity is a convex function of the stochastic channel
matrix. Since the more widely studied model of an independent identically
distributed (i.i.d.) deletion channel is a particular case, as an immediate
corollary to this result we also argue that the i.i.d. deletion channel
capacity is a convex function of the deletion probability. We further use this
result to improve the existing capacity upper bounds on the deletion channel by
a proper "convexification" argument. In particular, we prove that the capacity
of the deletion channel, as the deletion probability d --> 1, is upper bounded
by $0.4143(1-d)$ (which was also observed by a different (weaker) recent
result).
|
1102.2223
|
On Inverses for Quadratic Permutation Polynomials over Integer Rings
|
cs.IT math.IT
|
Quadratic permutation polynomial interleavers over integer rings have
recently received attention in practical turbo coding systems from deep space
applications to mobile communications. In this correspondence, a necessary and
sufficient condition that determines the least degree inverse of a quadratic
permutation polynomial is proven. Moreover, an algorithm is provided to
explicitly compute the inverse polynomials.
|
1102.2250
|
Modeling the pairwise key distribution scheme in the presence of
unreliable links
|
cs.IT math.CO math.IT
|
We investigate the secure connectivity of wireless sensor networks under the
pairwise key distribution scheme of Chan et al.. Unlike recent work which was
carried out under the assumption of full visibility, here we assume a
(simplified) communication model where unreliable wireless links are
represented as on/off channels. We present conditions on how to scale the model
parameters so that the network i) has no secure node which is isolated and ii)
is securely connected, both with high probability when the number of sensor
nodes becomes large. The results are given in the form of zero-one laws, and
exhibit significant differences with corresponding results in the full
visibility case. Through simulations these zero-one laws are shown to be valid
also under a more realistic communication model, i.e., the disk model.
|
1102.2254
|
Matrix completion with column manipulation: Near-optimal
sample-robustness-rank tradeoffs
|
stat.ML cs.IT math.IT
|
This paper considers the problem of matrix completion when some number of the
columns are completely and arbitrarily corrupted, potentially by a malicious
adversary. It is well-known that standard algorithms for matrix completion can
return arbitrarily poor results, if even a single column is corrupted. One
direct application comes from robust collaborative filtering. Here, some number
of users are so-called manipulators who try to skew the predictions of the
algorithm by calibrating their inputs to the system. In this paper, we develop
an efficient algorithm for this problem based on a combination of a trimming
procedure and a convex program that minimizes the nuclear norm and the
$\ell_{1,2}$ norm. Our theoretical results show that given a vanishing fraction
of observed entries, it is nevertheless possible to complete the underlying
matrix even when the number of corrupted columns grows. Significantly, our
results hold without any assumptions on the locations or values of the observed
entries of the manipulated columns. Moreover, we show by an
information-theoretic argument that our guarantees are nearly optimal in terms
of the fraction of sampled entries on the authentic columns, the fraction of
corrupted columns, and the rank of the underlying matrix. Our results therefore
sharply characterize the tradeoffs between sample, robustness and rank in
matrix completion.
|
1102.2284
|
Competitive Use of Multiple Antennas
|
cs.IT math.IT
|
A game theoretic framework is presented to analyze the problem of finding the
optimal number of data streams to transmit in a multi-user MIMO scenario, where
both the transmitters and receivers are equipped with multiple antennas.
Without channel state information (CSI) at any transmitter, and using outage
capacity as the utility function with zero-forcing receiver, each user is shown
to transmit a single data stream at Nash equilibrium in the presence of
sufficient number of users. Transmitting a single data stream is also shown to
be optimal in terms of maximizing the sum of the outage capacities in the
presence of sufficient number of users. With CSI available at each transmitter,
and using the number of successful bits per Joule of energy as the utility
function, at Nash equilibrium, each user is shown to transmit a single data
stream on the best eigen-mode that requires the least transmit power to achieve
a fixed signal-to-interference ratio. Using the concept of locally gross
direction preserving maps, existence of Nash equilibrium is shown when the
number of successful bits per Joule of energy is used as the utility function.
|
1102.2332
|
A Fast Measurement based fixed-point Quantum Search Algorithm
|
cs.DB quant-ph
|
Generic quantum search algorithm searches for target entity in an unsorted
database by repeatedly applying canonical Grover's quantum rotation transform
to reach near the vicinity of the target entity represented by a basis state in
the Hilbert space associated with the qubits. Thus, when qubits are measured,
there is a high probability of finding the target entity. However, the number
of times quantum rotation transform is to be applied for reaching near the
vicinity of the target is a function of the number of target entities present
in the unsorted database, which is generally unknown. A wrong estimate of the
number of target entities can lead to overshooting or undershooting the
targets, thus reducing the success probability. Some proposals have been made
to overcome this limitation. These proposals either employ quantum counting to
estimate the number of solutions or fixed point schemes. This paper proposes a
new scheme for stopping the application of quantum rotation transformation on
reaching near the targets by measurement and subsequent processing to estimate
the distance of the state vector from the target states. It ensures a success
probability, which is at least greater than half for all the ratios of the
number of target entities to the total number of entities in a database, which
are less than half. The search problem is trivial for remaining possible
ratios. The proposed scheme is simpler than quantum counting and more efficient
than the known fixed-point schemes. It has same order of computational
complexity as canonical Grover's search algorithm but is slow by a factor of
two and requires an additional ancilla qubit.
|
1102.2334
|
Weak KAM theoretic aspects for nonregular commuting Hamiltonians
|
math.AP cs.SY math.OC
|
In this paper we consider the notion of commutation for a pair of continuous
and convex Hamiltonians, given in terms of commutation of their Lax- Oleinik
semigroups. This is equivalent to the solvability of an associated multi- time
Hamilton-Jacobi equation. We examine the weak KAM theoretic aspects of the
commutation property and show that the two Hamiltonians have the same weak KAM
solutions and the same Aubry set, thus generalizing a result recently obtained
by the second author for Tonelli Hamiltonians. We make a further step by
proving that the Hamiltonians admit a common critical subsolution, strict
outside their Aubry set. This subsolution can be taken of class C^{1,1} in the
Tonelli case. To prove our main results in full generality, it is crucial to
establish suitable differentiability properties of the critical subsolutions on
the Aubry set. These latter results are new in the purely continuous case and
of independent interest.
|
1102.2336
|
Opinions within Media, Power and Gossip
|
cs.SI cs.AI physics.soc-ph
|
Despite the increasing diffusion of the Internet technology, TV remains the
principal medium of communication. People's perceptions, knowledge, beliefs and
opinions about matter of facts get (in)formed through the information reported
on by the mass-media. However, a single source of information (and consensus)
could be a potential cause of anomalies in the structure and evolution of a
society. Hence, as the information available (and the way it is reported) is
fundamental for our perceptions and opinions, the definition of conditions
allowing for a good information to be disseminated is a pressing challenge. In
this paper starting from a report on the last Italian political campaign in
2008, we derive a socio-cognitive computational model of opinion dynamics where
agents get informed by different sources of information. Then, a what-if
analysis, performed trough simulations on the model's parameters space, is
shown. In particular, the scenario implemented includes three main streams of
information acquisition, differing in both the contents and the perceived
reliability of the messages spread. Agents' internal opinion is updated either
by accessing one of the information sources, namely media and experts, or by
exchanging information with one another. They are also endowed with cognitive
mechanisms to accept, reject or partially consider the acquired information.
|
1102.2350
|
The best possible upper bound on the probability of undetected error for
linear codes of full support
|
cs.IT math.IT
|
There is a known best possible upper bound on the probability of undetected
error for linear codes. The $[n,k;q]$ codes with probability of undetected
error meeting the bound have support of size $k$ only. In this note, linear
codes of full support ($=n$) are studied. A best possible upper bound on the
probability of undetected error for such codes is given, and the codes with
probability of undetected error meeting this bound are characterized.
|
1102.2361
|
Convergence of type-symmetric and cut-balanced consensus seeking systems
(extended version)
|
cs.SY cs.MA math.OC
|
We consider continuous-time consensus seeking systems whose time-dependent
interactions are cut-balanced, in the following sense: if a group of agents
influences the remaining ones, the former group is also influenced by the
remaining ones by at least a proportional amount. Models involving symmetric
interconnections and models in which a weighted average of the agent values is
conserved are special cases. We prove that such systems always converge. We
give a sufficient condition on the evolving interaction topology for the limit
values of two agents to be the same. Conversely, we show that if our condition
is not satisfied, then these limits are generically different. These results
allow treating systems where the agent interactions are a priori unknown, e.g.,
random or determined endogenously by the agent values. We also derive
corresponding results for discrete-time systems.
|
1102.2382
|
A Comparison of Two Human Brain Tumor Segmentation Methods for MRI Data
|
cs.CV physics.med-ph
|
The most common primary brain tumors are gliomas, evolving from the cerebral
supportive cells. For clinical follow-up, the evaluation of the preoperative
tumor volume is essential. Volumetric assessment of tumor volume with manual
segmentation of its outlines is a time-consuming process that can be overcome
with the help of computerized segmentation methods. In this contribution, two
methods for World Health Organization (WHO) grade IV glioma segmentation in the
human brain are compared using magnetic resonance imaging (MRI) patient data
from the clinical routine. One method uses balloon inflation forces, and relies
on detection of high intensity tumor boundaries that are coupled with the use
of contrast agent gadolinium. The other method sets up a directed and weighted
graph and performs a min-cut for optimal segmentation results. The ground truth
of the tumor boundaries - for evaluating the methods on 27 cases - is manually
extracted by neurosurgeons with several years of experience in the resection of
gliomas. A comparison is performed using the Dice Similarity Coefficient (DSC),
a measure for the spatial overlap of different segmentation results.
|
1102.2395
|
Matching, Merging and Structural Properties of Data Base Category
|
cs.DB cs.LO math.CT
|
Main contribution of this paper is an investigation of expressive power of
the database category DB. An object in this category is a database-instance
(set of n-ary relations). Morphisms are not functions but have complex tree
structures based on a set of complex query computations. They express the
semantics of view-based mappings between databases. The higher (logical) level
scheme mappings between databases, usually written in some high expressive
logical language, may be functorially translated into this base "computation"
DB category . The behavioral point of view for databases is assumed, with
behavioural equivalence of databases corresponding to isomorphism of objects in
DB category. The introduced observations, which are view-based computations
without side-effects, are based (from Universal algebra) on monad endofunctor
T, which is the closure operator for objects and for morphisms also. It was
shown that DB is symmetric (with a bijection between arrows and objects)
2-category, equal to its dual, complete and cocomplete. In this paper we
demonstrate that DB is concrete, locally small and finitely presentable.
Moreover, it is enriched over itself monoidal symmetric category with a tensor
products for matching, and has a parameterized merging database operation. We
show that it is an algebraic lattice and we define a database metric space and
a subobject classifier: thus, DB category is a monoidal elementary topos.
|
1102.2398
|
The Kirchhoff's Matrix-Tree Theorem revisited: counting spanning trees
with the quantum relative entropy
|
quant-ph cs.IT math.CO math.IT
|
By revisiting the Kirchhoff's Matrix-Tree Theorem, we give an exact formula
for the number of spanning trees of a graph in terms of the quantum relative
entropy between the maximally mixed state and another state specifically
obtained from the graph. We use properties of the quantum relative entropy to
prove tight bounds for the number of spanning trees in terms of basic
parameters like degrees and number of vertices.
|
1102.2413
|
Optimal prefix codes for pairs of geometrically-distributed random
variables
|
cs.IT math.IT
|
Optimal prefix codes are studied for pairs of independent, integer-valued
symbols emitted by a source with a geometric probability distribution of
parameter $q$, $0{<}q{<}1$. By encoding pairs of symbols, it is possible to
reduce the redundancy penalty of symbol-by-symbol encoding, while preserving
the simplicity of the encoding and decoding procedures typical of Golomb codes
and their variants. It is shown that optimal codes for these so-called
two-dimensional geometric distributions are \emph{singular}, in the sense that
a prefix code that is optimal for one value of the parameter $q$ cannot be
optimal for any other value of $q$. This is in sharp contrast to the
one-dimensional case, where codes are optimal for positive-length intervals of
the parameter $q$. Thus, in the two-dimensional case, it is infeasible to give
a compact characterization of optimal codes for all values of the parameter
$q$, as was done in the one-dimensional case. Instead, optimal codes are
characterized for a discrete sequence of values of $q$ that provide good
coverage of the unit interval. Specifically, optimal prefix codes are described
for $q=2^{-1/k}$ ($k\ge 1$), covering the range $q\ge 1/2$, and $q=2^{-k}$
($k>1$), covering the range $q<1/2$. The described codes produce the expected
reduction in redundancy with respect to the one-dimensional case, while
maintaining low complexity coding operations.
|
1102.2423
|
Social network dynamics of face-to-face interactions
|
physics.soc-ph cond-mat.dis-nn cond-mat.stat-mech cs.SI
|
The recent availability of data describing social networks is changing our
understanding of the "microscopic structure" of a social tie. A social tie
indeed is an aggregated outcome of many social interactions such as
face-to-face conversations or phone-calls. Analysis of data on face-to-face
interactions shows that such events, as many other human activities, are
bursty, with very heterogeneous durations. In this paper we present a model for
social interactions at short time scales, aimed at describing contexts such as
conference venues in which individuals interact in small groups. We present a
detailed anayltical and numerical study of the model's dynamical properties,
and show that it reproduces important features of empirical data. The model
allows for many generalizations toward an increasingly realistic description of
social interactions. In particular in this paper we investigate the case where
the agents have intrinsic heterogeneities in their social behavior, or where
dynamic variations of the local number of individuals are included. Finally we
propose this model as a very flexible framework to investigate how dynamical
processes unfold in social networks.
|
1102.2453
|
Reducing the Number of Elements in Linear and Planar Antenna Arrays with
Sparse Constraint Optimization
|
cs.IT math.IT
|
This paper has been withdrawn by the authors. I will do the major revision.
|
1102.2467
|
Universal Learning Theory
|
cs.LG cs.IT math.IT
|
This encyclopedic article gives a mini-introduction into the theory of
universal learning, founded by Ray Solomonoff in the 1960s and significantly
developed and extended in the last decade. It explains the spirit of universal
learning, but necessarily glosses over technical subtleties.
|
1102.2468
|
Algorithmic Randomness as Foundation of Inductive Reasoning and
Artificial Intelligence
|
cs.IT cs.AI cs.CC math.IT
|
This article is a brief personal account of the past, present, and future of
algorithmic randomness, emphasizing its role in inductive inference and
artificial intelligence. It is written for a general audience interested in
science and philosophy. Intuitively, randomness is a lack of order or
predictability. If randomness is the opposite of determinism, then algorithmic
randomness is the opposite of computability. Besides many other things, these
concepts have been used to quantify Ockham's razor, solve the induction
problem, and define intelligence.
|
1102.2490
|
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond
|
math.ST cs.LG cs.SY math.OC stat.TH
|
This paper presents a finite-time analysis of the KL-UCB algorithm, an
online, horizon-free index policy for stochastic bandit problems. We prove two
distinct results: first, for arbitrary bounded rewards, the KL-UCB algorithm
satisfies a uniformly better regret bound than UCB or UCB2; second, in the
special case of Bernoulli rewards, it reaches the lower bound of Lai and
Robbins. Furthermore, we show that simple adaptations of the KL-UCB algorithm
are also optimal for specific classes of (possibly unbounded) rewards,
including those generated from exponential families of distributions. A
large-scale numerical study comparing KL-UCB with its main competitors (UCB,
UCB2, UCB-Tuned, UCB-V, DMED) shows that KL-UCB is remarkably efficient and
stable, including for short time horizons. KL-UCB is also the only method that
always performs better than the basic UCB policy. Our regret bounds rely on
deviations results of independent interest which are stated and proved in the
Appendix. As a by-product, we also obtain an improved regret bound for the
standard UCB algorithm.
|
1102.2498
|
Two-Unicast Wireless Networks: Characterizing the Degrees-of-Freedom
|
cs.IT math.IT
|
We consider two-source two-destination (i.e., two-unicast) multi-hop wireless
networks that have a layered structure with arbitrary connectivity. We show
that, if the channel gains are chosen independently according to continuous
distributions, then, with probability 1, two-unicast layered Gaussian networks
can only have 1, 3/2 or 2 sum degrees-of-freedom (unless both
source-destination pairs are disconnected, in which case no degrees-of-freedom
can be achieved). We provide sufficient and necessary conditions for each case
based on network connectivity and a new notion of source-destination paths with
manageable interference. Our achievability scheme is based on forwarding the
received signals at all nodes, except for a small fraction of them in at most
two key layers. Hence, we effectively create a "condensed network" that has at
most four layers (including the sources layer and the destinations layer). We
design the transmission strategies based on the structure of this condensed
network. The converse results are obtained by developing information-theoretic
inequalities that capture the structures of the network connectivity. Finally,
we extend this result and characterize the full degrees-of-freedom region of
two-unicast layered wireless networks.
|
1102.2504
|
Cognitive Multiple Access Network with Outage Margin in the Primary
System
|
cs.IT math.IT
|
This paper investigates the problem of spectrally efficient operation of a
multiuser uplink cognitive radio system in the presence of a single primary
link. The secondary system applies opportunistic interference cancelation (OIC)
and decode the primary signal when such an opportunity is created. We derive
the achievable rate in the secondary system when OIC is used. This scheme has a
practical significance, since it enables rate adaptation without requiring any
action from the primary system. The \emph{exact} expressions for outage
probability of the primary user are derived, when the primary system is exposed
to interference from secondary users. Moreover, approximated formulas and tight
lower and upper bounds for the ergodic sum-rate capacity of the secondary
network are found. Next, the power allocation is investigated in the secondary
system for maximizing the sum-rate under an outage constraint at the primary
system. We formulate the power optimization problem in various scenarios
depending on the availability of channel state information and the type of
power constraints, and propose a set of simple solutions. Finally, the
analytical results are confirmed by simulations, indicating both the accuracy
of the analysis, and the fact that the spectral-efficient, low-complexity,
flexible, and high-performing cognitive radio can be designed based on the
proposed schemes.
|
1102.2506
|
Opportunistic Relaying for Space-Time Coded Cooperation with Multiple
Antenna Terminals
|
cs.IT math.IT
|
We consider a wireless relay network with multiple antenna terminals over
Rayleigh fading channels, and apply distributed space-time coding (DSTC) in
amplify-and-forward (A&F) mode. The A&F scheme is used in a way that each relay
transmits a scaled version of the linear combination of the received symbols.
It turns out that, combined with power allocation in the relays, A&F DSTC
results in an opportunistic relaying scheme, in which only the best relay is
selected to retransmit the source's space-time coded signal. Furthermore,
assuming the knowledge of source-relay CSI at the source node, we design an
efficient power allocation which outperforms uniform power allocation across
the source antennas. Next, assuming M-PSK or M-QAM modulations, we analyze the
performance of the proposed cooperative diversity transmission schemes in a
wireless relay networks with the multiple-antenna source and destination. We
derive the probability density function (PDF) of the received SNR at the
destination. Then, the PDF is used to determine the symbol error rate (SER) in
Rayleigh fading channels. We derived closed-form approximations of the average
SER in the high SNR scenario, from which we find the diversity order of system
RminfNs;Ndg, where R, Ns, and Nd are the number of the relays, source antennas,
and destination antennas, respectively. Simulation results show that the
proposed system obtain more than 6 dB gain in SNR over A&F MIMO DSTC for BER
10^{-4}, when R = 2, Ns = 2, and Nd = 1.
|
1102.2516
|
High Throughput Random Access via Codes on Graphs: Coded Slotted ALOHA
|
cs.IT math.IT
|
In this paper, coded slotted ALOHA (CSA) is introduced as a powerful random
access scheme to the MAC frame. In CSA, the burst a generic user wishes to
transmit in the MAC frame is first split into segments, and these segments are
then encoded through a local a packet-oriented code prior to transmission. On
the receiver side, iterative interference cancellation combined with decoding
of the local code is performed to recover from collisions. The new scheme
generalizes the previously proposed irregular repetition slotted ALOHA (IRSA)
technique, based on a simple repetition of the users' bursts. An interpretation
of the CSA interference cancellation process as an iterative erasure decoding
process over a sparse bipartite graph is identified, and the corresponding
density evolution equations derived. Based on these equations, asymptotically
optimal CSA schemes are designed for several rates and their performance for a
finite number of users investigated through simulation and compared to IRSA
competitors. Throughputs as high as 0.8 are demonstrated. The new scheme turns
out to be a good candidate in contexts where power efficiency is required.
|
1102.2524
|
Multicriteria Steiner Tree Problem for Communication Network
|
cs.DS cs.AI cs.NI math.OC
|
This paper addresses combinatorial optimization scheme for solving the
multicriteria Steiner tree problem for communication network topology design
(e.g., wireless mesh network). The solving scheme is based on several models:
multicriteria ranking, clustering, minimum spanning tree, and minimum Steiner
tree problem. An illustrative numerical example corresponds to designing a
covering long-distance Wi-Fi network (static Ad-Hoc network). The set of
criteria (i.e., objective functions) involves the following: total cost, total
edge length, overall throughput (capacity), and estimate of QoS. Obtained
computing results show the suggested solving scheme provides good network
topologies which can be compared with minimum spanning trees.
|
1102.2536
|
Lower bounds on Information Divergence
|
cs.IT math.IT math.PR
|
In this paper we establish lower bounds on information divergence from a
distribution to certain important classes of distributions as Gaussian,
exponential, Gamma, Poisson, geometric, and binomial. These lower bounds are
tight and for several convergence theorems where a rate of convergence can be
computed, this rate is determined by the lower bounds proved in this paper.
General techniques for getting lower bounds in terms of moments are developed.
|
1102.2551
|
Yield Optimization of Display Advertising with Ad Exchange
|
math.OC cs.DS cs.SY
|
In light of the growing market of Ad Exchanges for the real-time sale of
advertising slots, publishers face new challenges in choosing between the
allocation of contract-based reservation ads and spot market ads. In this
setting, the publisher should take into account the tradeoff between short-term
revenue from an Ad Exchange and quality of allocating reservation ads. In this
paper, we formalize this combined optimization problem as a stochastic control
problem and derive an efficient policy for online ad allocation in settings
with general joint distribution over placement quality and exchange bids. We
prove asymptotic optimality of this policy in terms of any trade-off between
quality of delivered reservation ads and revenue from the exchange, and provide
a rigorous bound for its convergence rate to the optimal policy. We also give
experimental results on data derived from real publisher inventory, showing
that our policy can achieve any pareto-optimal point on the quality vs. revenue
curve. Finally, we study a parametric training-based algorithm in which instead
of learning the dual variables from a sample data (as is done in non-parametric
training-based algorithms), we learn the parameters of the distribution and
construct those dual variables from the learned parameter values. We compare
parametric and non-parametric ways to estimate from data both analytically and
experimentally in the special case without the ad exchange, and show that
though both methods converge to the optimal policy as the sample size grows,
our parametric method converges faster, and thus performs better on smaller
samples.
|
1102.2559
|
Toward Measuring the Scaling of Genetic Programming
|
cs.NE
|
Several genetic programming systems are created, each solving a different
problem. In these systems, the median number of generations G needed to evolve
a working program is measured. The behavior of G is observed as the difficulty
of the problem is increased. In these systems, the density D of working
programs in the universe of all possible programs is measured. The relationship
G ~ 1/sqrt(D) is observed to approximately hold for two program-like systems.
For parallel systems (systems that look like several independent programs
evolving in parallel), the relationship G ~ 1/(n ln n) is observed to
approximately hold. Finally, systems that are anti-parallel are considered.
|
1102.2566
|
Key Reduction of McEliece's Cryptosystem Using List Decoding
|
cs.CR cs.IT math.IT
|
Different variants of the code-based McEliece cryptosystem were pro- posed to
reduce the size of the public key. All these variants use very structured
codes, which open the door to new attacks exploiting the underlying structure.
In this paper, we show that the dyadic variant can be designed to resist all
known attacks. In light of a new study on list decoding algorithms for binary
Goppa codes, we explain how to increase the security level for given public
keysizes. Using the state-of-the-art list decoding algorithm instead of unique
decoding, we exhibit a keysize gain of about 4% for the standard McEliece
cryptosystem and up to 21% for the adjusted dyadic variant.
|
1102.2568
|
Frequency characteristics based on describing function method for
differentiators
|
cs.SY
|
In this paper, describing function method is used to analyze the
characteristics and parameters selection of differentiators. Nonlinear
differentiator is an effective compensation to linear differentiator, and
hybrid differentiator consisting of linear and nonlinear parts is the
combination of both advantages of linear and nonlinear differentiators. The
merits of the hybrid differentiator include its simplicity, rapid convergence
at all times, and restraining noises effectively. The methods are confirmed by
some examples.
|
1102.2593
|
Codes and Designs Related to Lifted MRD Codes
|
cs.IT cs.DM math.IT
|
Lifted maximum rank distance (MRD) codes, which are constant dimension codes,
are considered. It is shown that a lifted MRD code can be represented in such a
way that it forms a block design known as a transversal design. A slightly
different representation of this design makes it similar to a $q-$analog of a
transversal design. The structure of these designs is used to obtain upper
bounds on the sizes of constant dimension codes which contain a lifted MRD
code. Codes which attain these bounds are constructed. These codes are the
largest known codes for the given parameters. These transversal designs can be
also used to derive a new family of linear codes in the Hamming space. Bounds
on the minimum distance and the dimension of such codes are given.
|
1102.2598
|
The Dispersion of Lossy Source Coding
|
cs.IT math.IT
|
In this work we investigate the behavior of the minimal rate needed in order
to guarantee a given probability that the distortion exceeds a prescribed
threshold, at some fixed finite quantization block length. We show that the
excess coding rate above the rate-distortion function is inversely proportional
(to the first order) to the square root of the block length. We give an
explicit expression for the proportion constant, which is given by the inverse
Q-function of the allowed excess distortion probability, times the square root
of a constant, termed the excess distortion dispersion. This result is the dual
of a corresponding channel coding result, where the dispersion above is the
dual of the channel dispersion. The work treats discrete memoryless sources, as
well as the quadratic-Gaussian case.
|
1102.2599
|
Rapid-convergent nonlinear differentiator
|
cs.SY
|
A nonlinear differentiator being fit for rapid convergence is presented,
which is based on singular perturbation technique. The differentiator design
can not only sufficiently reduce the chattering phenomenon of derivative
estimation by introducing a continuous power function, but the dynamical
performances are also improved by adding linear correction terms to the
nonlinear ones. Moreover, strong robustness ability is obtained by integrating
nonlinear items and the linear filter. The merits of the rapid-convergent
differentiator include the excellent dynamical performances, restraining noises
sufficiently, avoiding the chattering phenomenon and being not based on system
model. The theoretical results are confirmed by computer simulations and an
experiment.
|
1102.2600
|
High-order integral-chain differentiator and application to acceleration
feedback
|
cs.SY
|
The equivalence between integral-chain differentiator and usual high-gain
differentiator is given under suitable coordinate transformation.
Integral-chain differentiator can restrain noises more thoroughly than usual
high-gain linear differentiator. In integral-chain differentiator, disturbances
only exist in the last differential equation and can be restrained through each
layer of integrator. Moreover, a nonlinear integral-chain differentiator is
designed which is the expansion of linear integral-chain differentiator.
Finally, a 3-order differentiator is applied to the estimation of acceleration
for a second-order uncertain system.
|
1102.2602
|
A New Method for Variable Elimination in Systems of Inequations
|
cs.IT cs.DS math.IT
|
In this paper, we present a new method for variable elimination in systems of
inequations which is much faster than the Fourier-Motzkin Elimination (FME)
method. In our method, a linear Diophantine problem is introduced which is dual
to our original problem. The new Diophantine system is then solved, and the
final result is calculated by finding the dual inequations system. Our new
method uses the algorithm Normaliz to find the Hilbert basis of the solution
space of the given Diophantine problem. We introduce a problem in the
interference channel with multiple nodes and solve it with our new method.
Next, we generalize our method to all problems involving FME and in the end we
compare our method with the previous method. We show that our method has many
advantages in comparison to the previous method. It does not produce many of
the redundant answers of the FME method. It also solves the whole problem in
one step whereas the previous method uses a step by step approach in
eliminating each auxiliary variable.
|
1102.2615
|
Guaranteeing Convergence of Iterative Skewed Voting Algorithms for Image
Segmentation
|
math.FA cs.CV nlin.CG
|
In this paper we provide rigorous proof for the convergence of an iterative
voting-based image segmentation algorithm called Active Masks. Active Masks
(AM) was proposed to solve the challenging task of delineating punctate
patterns of cells from fluorescence microscope images. Each iteration of AM
consists of a linear convolution composed with a nonlinear thresholding; what
makes this process special in our case is the presence of additive terms whose
role is to "skew" the voting when prior information is available. In real-world
implementation, the AM algorithm always converges to a fixed point. We study
the behavior of AM rigorously and present a proof of this convergence. The key
idea is to formulate AM as a generalized (parallel) majority cellular
automaton, adapting proof techniques from discrete dynamical systems.
|
1102.2620
|
Predicting economic market crises using measures of collective panic
|
q-fin.ST cs.SI physics.soc-ph
|
Predicting panic is of critical importance in many areas of human and animal
behavior, notably in the context of economics. The recent financial crisis is a
case in point. Panic may be due to a specific external threat, or
self-generated nervousness. Here we show that the recent economic crisis and
earlier large single-day panics were preceded by extended periods of high
levels of market mimicry --- direct evidence of uncertainty and nervousness,
and of the comparatively weak influence of external news. High levels of
mimicry can be a quite general indicator of the potential for self-organized
crises.
|
1102.2623
|
Egomunities, Exploring Socially Cohesive Person-based Communities
|
cs.SI cs.NI physics.soc-ph
|
In the last few years, there has been a great interest in detecting
overlapping communities in complex networks, which is understood as dense
groups of nodes featuring a low outbound density. To date, most methods used to
compute such communities stem from the field of disjoint community detection by
either extending the concept of modularity to an overlapping context or by
attempting to decompose the whole set of nodes into several possibly
overlapping subsets. In this report we take an orthogonal approach by
introducing a metric, the cohesion, rooted in sociological considerations. The
cohesion quantifies the community-ness of one given set of nodes, based on the
notions of triangles - triplets of connected nodes - and weak ties, instead of
the classical view using only edge density. A set of nodes has a high cohesion
if it features a high density of triangles and intersects few triangles with
the rest of the network. As such, we introduce a numerical characterization of
communities: sets of nodes featuring a high cohesion. We then present a new
approach to the problem of overlapping communities by introducing the concept
of ego-munities, which are subjective communities centered around a given node,
specifically inside its neighborhood. We build upon the cohesion to construct a
heuristic algorithm which outputs a node's ego-munities by attempting to
maximize their cohesion. We illustrate the pertinence of our method with a
detailed description of one person's ego-munities among Facebook friends. We
finally conclude by describing promising applications of ego-munities such as
information inference and interest recommendations, and present a possible
extension to cohesion in the case of weighted networks.
|
1102.2624
|
Classical communication over a quantum interference channel
|
quant-ph cs.IT math.IT
|
Calculating the capacity of interference channels is a notorious open problem
in classical information theory. Such channels have two senders and two
receivers, and each sender would like to communicate with a partner receiver.
The capacity of such channels is known exactly in the settings of "very strong"
and "strong" interference, while the Han-Kobayashi coding strategy gives the
best known achievable rate region in the general case. Here, we introduce and
study the quantum interference channel, a natural generalization of the
interference channel to the setting of quantum information theory. We restrict
ourselves for the most part to channels with two classical inputs and two
quantum outputs in order to simplify the presentation of our results (though
generalizations of our results to channels with quantum inputs are
straightforward). We are able to determine the exact classical capacity of this
channel in the settings of "very strong" and "strong" interference, by
exploiting Winter's successive decoding strategy and a novel two-sender quantum
simultaneous decoder, respectively. We provide a proof that a Han-Kobayashi
strategy is achievable with Holevo information rates, up to a conjecture
regarding the existence of a three-sender quantum simultaneous decoder. This
conjecture holds for a special class of quantum multiple access channels with
average output states that commute, and we discuss some other variations of the
conjecture that hold. Finally, we detail a connection between the quantum
interference channel and prior work on the capacity of bipartite unitary gates.
|
1102.2627
|
The free space optical interference channel
|
quant-ph cs.IT math.IT
|
Semiclassical models for multiple-user optical communication cannot assess
the ultimate limits on reliable communication as permitted by the laws of
physics. In all optical communications settings that have been analyzed within
a quantum framework so far, the gaps between the quantum limit to the capacity
and the Shannon limit for structured receivers become most significant in the
low photon-number regime. Here, we present a quantum treatment of a
multiple-transmitter multiple-receiver multi-spatial-mode free-space
interference channel with diffraction-limited loss and a thermal background. We
consider the performance of a laser-light (coherent state) encoding in
conjunction with various detection strategies such as homodyne, heterodyne, and
joint detection. Joint detection outperforms both homodyne and heterodyne
detection whenever the channel exhibits "very strong" interference. We
determine the capacity region for homodyne or heterodyne detection when the
channel has "strong" interference, and we conjecture the existence of a joint
detection strategy that outperforms the former two strategies in this case.
Finally, we determine the Han-Kobayashi achievable rate regions for both
homodyne and heterodyne detection and compare them to a region achievable by a
conjectured joint detection strategy. In these latter cases, we determine
achievable rate regions if the receivers employ a recently discovered
min-entropy quantum simultaneous decoder.
|
1102.2641
|
Improved Redundancy Bounds for Exponential Objectives
|
cs.IT math.IT
|
We present new lower and upper bounds for the compression rate of binary
prefix codes optimized over memoryless sources according to two related
exponential codeword length objectives. The objectives explored here are
exponential-average length and exponential-average redundancy. The first of
these relates to various problems involving queueing, uncertainty, and lossless
communications, and it can be reduced to the second, which has properties more
amenable to analysis. These bounds, some of which are tight, are in terms of a
form of entropy and/or the probability of an input symbol, improving on
recently discovered bounds of similar form. We also observe properties of
optimal codes over the exponential-average redundancy utility.
|
1102.2654
|
PORGY: Strategy-Driven Interactive Transformation of Graphs
|
cs.CE cs.SE
|
This paper investigates the use of graph rewriting systems as a modelling
tool, and advocates the embedding of such systems in an interactive
environment. One important application domain is the modelling of biochemical
systems, where states are represented by port graphs and the dynamics is driven
by rules and strategies. A graph rewriting tool's capability to interactively
explore the features of the rewriting system provides useful insights into
possible behaviours of the model and its properties. We describe PORGY, a
visual and interactive tool we have developed to model complex systems using
port graphs and port graph rewrite rules guided by strategies, and to navigate
in the derivation history. We demonstrate via examples some functionalities
provided by PORGY.
|
1102.2670
|
Online Least Squares Estimation with Self-Normalized Processes: An
Application to Bandit Problems
|
cs.AI
|
The analysis of online least squares estimation is at the heart of many
stochastic sequential decision making problems. We employ tools from the
self-normalized processes to provide a simple and self-contained proof of a
tail bound of a vector-valued martingale. We use the bound to construct a new
tighter confidence sets for the least squares estimate.
We apply the confidence sets to several online decision problems, such as the
multi-armed and the linearly parametrized bandit problems. The confidence sets
are potentially applicable to other problems such as sleeping bandits,
generalized linear bandits, and other linear control problems.
We improve the regret bound of the Upper Confidence Bound (UCB) algorithm of
Auer et al. (2002) and show that its regret is with high-probability a problem
dependent constant. In the case of linear bandits (Dani et al., 2008), we
improve the problem dependent bound in the dimension and number of time steps.
Furthermore, as opposed to the previous result, we prove that our bound holds
for small sample sizes, and at the same time the worst case bound is improved
by a logarithmic factor and the constant is improved.
|
1102.2673
|
Environmental benefits of enhanced surveillance technology on airport
departure operations
|
cs.SY
|
Airport departure operations constitute an important source of airline delays
and passenger frustration. Excessive surface traffic is the cause of increased
controller and pilot workload; It is also the source of increased emissions; It
worsens traffic safety and often does not yield improved runway throughput.
Acknowledging this fact, this paper explores some of the feedback mechanisms by
which airport traffic can be optimized in real time according to its current
degree of congestion. In particular, it examines the environmnetal benefits
that improved surveillance technologies can bring in the context of gate- or
spot-release aircraft strategies. It is shown that improvements can lead yield
4% to 6% emission reductions for busy airports like New-York La Guardia or
Seattle Tacoma. These benefits come on top of the benefits already obtained by
adopting threshold strategies currently under evaluation.
|
1102.2677
|
Measurement Bounds for Sparse Signal Ensembles via Graphical Models
|
cs.IT math.IT
|
In compressive sensing, a small collection of linear projections of a sparse
signal contains enough information to permit signal recovery. Distributed
compressive sensing (DCS) extends this framework by defining ensemble sparsity
models, allowing a correlated ensemble of sparse signals to be jointly
recovered from a collection of separately acquired compressive measurements. In
this paper, we introduce a framework for modeling sparse signal ensembles that
quantifies the intra- and inter-signal dependencies within and among the
signals. This framework is based on a novel bipartite graph representation that
links the sparse signal coefficients with the measurements obtained for each
signal. Using our framework, we provide fundamental bounds on the number of
noiseless measurements that each sensor must collect to ensure that the signals
are jointly recoverable.
|
1102.2678
|
Minimum Redundancy Coding for Uncertain Sources
|
cs.IT math.IT
|
Consider the set of source distributions within a fixed maximum relative
entropy with respect to a given nominal distribution. Lossless source coding
over this relative entropy ball can be approached in more than one way. A
problem previously considered is finding a minimax average length source code.
The minimizing players are the codeword lengths --- real numbers for arithmetic
codes, integers for prefix codes --- while the maximizing players are the
uncertain source distributions. Another traditional minimizing objective is the
first one considered here, maximum (average) redundancy. This problem reduces
to an extension of an exponential Huffman objective treated in the literature
but heretofore without direct practical application. In addition to these, this
paper examines the related problem of maximal minimax pointwise redundancy and
the problem considered by Gawrychowski and Gagie, which, for a sufficiently
small relative entropy ball, is equivalent to minimax redundancy. One can
consider both Shannon-like coding based on optimal real number ("ideal")
codeword lengths and a Huffman-like optimal prefix coding.
|
1102.2684
|
Chernoff information of exponential families
|
cs.IT cs.CV cs.IR math.IT
|
Chernoff information upper bounds the probability of error of the optimal
Bayesian decision rule for $2$-class classification problems. However, it turns
out that in practice the Chernoff bound is hard to calculate or even
approximate. In statistics, many usual distributions, such as Gaussians,
Poissons or frequency histograms called multinomials, can be handled in the
unified framework of exponential families. In this note, we prove that the
Chernoff information for members of the same exponential family can be either
derived analytically in closed form, or efficiently approximated using a simple
geodesic bisection optimization technique based on an exact geometric
characterization of the "Chernoff point" on the underlying statistical
manifold.
|
1102.2700
|
On (Partial) Unit Memory Codes Based on Gabidulin Codes
|
cs.IT math.IT
|
(Partial) Unit Memory ((P)UM) codes provide a powerful possibility to
construct convolutional codes based on block codes in order to achieve a high
decoding performance. In this contribution, a construction based on Gabidulin
codes is considered. This construction requires a modified rank metric, the
so-called sum rank metric. For the sum rank metric, the free rank distance, the
extended row rank distance and its slope are defined analogous to the extended
row distance in Hamming metric. Upper bounds for the free rank distance and the
slope of (P)UM codes in the sum rank metric are derived and an explicit
construction of (P)UM codes based on Gabidulin codes is given, achieving the
upper bound for the free rank distance.
|
1102.2702
|
On the Labeling Problem of Permutation Group Codes under the Infinity
Metric
|
cs.IT math.IT
|
Codes over permutations under the infinity norm have been recently suggested
as a coding scheme for correcting limited-magnitude errors in the rank
modulation scheme. Given such a code, we show that a simple relabeling
operation, which produces an isomorphic code, may drastically change the
minimal distance of the code. Thus, we may choose a code structure for
efficient encoding/decoding procedures, and then optimize the code's minimal
distance via relabeling.
We formally define the relabeling problem, and show that all codes may be
relabeled to get a minimal distance at most 2. The decision problem of whether
a code may be relabeled to distance 1 is shown to be NP-complete, and
calculating the best achievable minimal distance after relabeling is proved
hard to approximate.
Finally, we consider general bounds on the relabeling problem. We
specifically show the optimal relabeling distance of cyclic groups. A specific
case of a general probabilistic argument is used to show $\agl(p)$ may be
relabeled to a minimal distance of $p-O(\sqrt{p\ln p})$.
|
1102.2706
|
Blind source separation of convolutive mixtures of non circular linearly
modulated signals with unknown baud rates
|
cs.IT math.IT
|
This paper addresses the problem of blind separation of convolutive mixtures
of BPSK and circular linearly modulated signals with unknown (and possibly
different) baud rates and carrier frequencies. In previous works, we
established that the Constant Modulus Algorithm (CMA) is able to extract a
source from a convolutive mixture of circular linearly modulated signals. We
extend the analysis of the extraction capabilities of the CMA when the mixing
also contains BPSK signals. We prove that if the various source signals do not
share any non zero cyclic frequency nor any non conjugate cyclic frequencies,
the local minima of the constant modulus cost function are separating filters.
Unfortunately, the minimization of the Godard cost function generally fails
when considering BPSK signals that have the same rates and the same carrier
frequencies. This failure is due to the existence of non-separating local
minima of the Godard cost function. In order to achieve the separation, we
propose a simple modification of the Godard cost function which only requires
knowledge of the BPSK sources frequency offsets at the receiver side. We
provide various simulations of realistic digital communications scenarios that
support our theoretical statements.
|
1102.2731
|
Necessary and Sufficient Conditions for Distinguishability of Linear
Control Systems
|
math.OC cs.SY
|
Distinguishability takes a crucial rule in studying observability of hybrid
system such as switched system. Recently, for two linear systems, Lou and Si
gave a condition not only necessary but also sufficient to the
distinguishability of linear systems. However, the condition is not easy enough
to verify. This paper will give a new equivalent condition which is relatively
easy to verify.
|
1102.2734
|
The Treewidth of MDS and Reed-Muller Codes
|
cs.IT cs.DM math.IT
|
The constraint complexity of a graphical realization of a linear code is the
maximum dimension of the local constraint codes in the realization. The
treewidth of a linear code is the least constraint complexity of any of its
cycle-free graphical realizations. This notion provides a useful
parametrization of the maximum-likelihood decoding complexity for linear codes.
In this paper, we prove the surprising fact that for maximum distance separable
codes and Reed-Muller codes, treewidth equals trelliswidth, which, for a code,
is defined to be the least constraint complexity (or branch complexity) of any
of its trellis realizations. From this, we obtain exact expressions for the
treewidth of these codes, which constitute the only known explicit expressions
for the treewidth of algebraic codes.
|
1102.2738
|
Decision Theory with Prospect Interference and Entanglement
|
math-ph cs.AI math.MP physics.soc-ph quant-ph
|
We present a novel variant of decision making based on the mathematical
theory of separable Hilbert spaces. This mathematical structure captures the
effect of superposition of composite prospects, including many incorporated
intentions, which allows us to describe a variety of interesting fallacies and
anomalies that have been reported to particularize the decision making of real
human beings. The theory characterizes entangled decision making,
non-commutativity of subsequent decisions, and intention interference. We
demonstrate how the violation of the Savage's sure-thing principle, known as
the disjunction effect, can be explained quantitatively as a result of the
interference of intentions, when making decisions under uncertainty. The
disjunction effects, observed in experiments, are accurately predicted using a
theorem on interference alternation that we derive, which connects
aversion-to-uncertainty to the appearance of negative interference terms
suppressing the probability of actions. The conjunction fallacy is also
explained by the presence of the interference terms. A series of experiments
are analysed and shown to be in excellent agreement with a priori evaluation of
interference effects. The conjunction fallacy is also shown to be a sufficient
condition for the disjunction effect and novel experiments testing the combined
interplay between the two effects are suggested.
|
1102.2739
|
A General Framework for Development of the Cortex-like Visual Object
Recognition System: Waves of Spikes, Predictive Coding and Universal
Dictionary of Features
|
cs.CV cs.AI cs.LG cs.NE
|
This study is focused on the development of the cortex-like visual object
recognition system. We propose a general framework, which consists of three
hierarchical levels (modules). These modules functionally correspond to the V1,
V4 and IT areas. Both bottom-up and top-down connections between the
hierarchical levels V4 and IT are employed. The higher the degree of matching
between the input and the preferred stimulus, the shorter the response time of
the neuron. Therefore information about a single stimulus is distributed in
time and is transmitted by the waves of spikes. The reciprocal connections and
waves of spikes implement predictive coding: an initial hypothesis is generated
on the basis of information delivered by the first wave of spikes and is tested
with the information carried by the consecutive waves. The development is
considered as extraction and accumulation of features in V4 and objects in IT.
Once stored a feature can be disposed, if rarely activated. This cause update
of feature repository. Consequently, objects in IT are also updated. This
illustrates the growing process and dynamical change of topological structures
of V4, IT and connections between these areas.
|
1102.2743
|
Feature selection via simultaneous sparse approximation for person
specific face verification
|
cs.CV
|
There is an increasing use of some imperceivable and redundant local features
for face recognition. While only a relatively small fraction of them is
relevant to the final recognition task, the feature selection is a crucial and
necessary step to select the most discriminant ones to obtain a compact face
representation. In this paper, we investigate the sparsity-enforced
regularization-based feature selection methods and propose a multi-task feature
selection method for building person specific models for face verification. We
assume that the person specific models share a common subset of features and
novelly reformulated the common subset selection problem as a simultaneous
sparse approximation problem. To the best of our knowledge, it is the first
time to apply the sparsity-enforced regularization methods for person specific
face verification. The effectiveness of the proposed methods is verified with
the challenging LFW face databases.
|
1102.2748
|
Feature Selection via Sparse Approximation for Face Recognition
|
cs.CV cs.AI
|
Inspired by biological vision systems, the over-complete local features with
huge cardinality are increasingly used for face recognition during the last
decades. Accordingly, feature selection has become more and more important and
plays a critical role for face data description and recognition. In this paper,
we propose a trainable feature selection algorithm based on the regularized
frame for face recognition. By enforcing a sparsity penalty term on the minimum
squared error (MSE) criterion, we cast the feature selection problem into a
combinatorial sparse approximation problem, which can be solved by greedy
methods or convex relaxation methods. Moreover, based on the same frame, we
propose a sparse Ho-Kashyap (HK) procedure to obtain simultaneously the optimal
sparse solution and the corresponding margin vector of the MSE criterion. The
proposed methods are used for selecting the most informative Gabor features of
face images for recognition and the experimental results on benchmark face
databases demonstrate the effectiveness of the proposed methods.
|
1102.2749
|
Multi-task GLOH feature selection for human age estimation
|
cs.CV cs.AI
|
In this paper, we propose a novel age estimation method based on GLOH feature
descriptor and multi-task learning (MTL). The GLOH feature descriptor, one of
the state-of-the-art feature descriptor, is used to capture the age-related
local and spatial information of face image. As the exacted GLOH features are
often redundant, MTL is designed to select the most informative feature bins
for age estimation problem, while the corresponding weights are determined by
ridge regression. This approach largely reduces the dimensions of feature,
which can not only improve performance but also decrease the computational
burden. Experiments on the public available FG-NET database show that the
proposed method can achieve comparable performance over previous approaches
while using much fewer features.
|
1102.2761
|
Capacity of BICM Using (Bi-)Orthogonal Signal Constellations in
Impulse-Radio Ultra-Wideband Systems
|
cs.IT math.IT
|
Bit-interleaved coded modulation (BICM) using (bi-)orthogonal signals is
especially well suited for the application in impulse-radio ultra-wideband
transmission systems, which typically operate in the power-limited regime and
require a very low-complexity transmitter and receiver design. In this paper we
analyze the capacity of BICM using (bi-)orthogonal signals with coherent and
noncoherent detection and put particular focus on the power-limited or wideband
regime. We give analytical expressions for the ratio energy per bit vs. noise
power spectral density in the limit of infinite bandwidth and the respective
wideband slope, and thus, are able to quantify the loss incurred by the
restriction to BICM in contrast to coded modulation. The gained theoretical
insights allow to derive design rules for impulse-radio ultra-wideband
transmission systems.
|
1102.2768
|
Achievable Rate Region of Quantized Broadcast and MAC Channels
|
cs.IT math.IT
|
In this paper, we study the achievable rate region of Gaussian multiuser
channels with the messages transmitted being from finite input alphabets and
the outputs being {\em quantized at the receiver}. In particular, we focus on
the achievable rate region of $i)$ Gaussian broadcast channel (GBC) and $ii)$
Gaussian multiple access channel (GMAC). First, we study the achievable rate
region of two-user GBC when the messages to be transmitted to both the users
take values from finite signal sets and the received signal is quantized at
both the users. We refer to this channel as {\em quantized broadcast channel
(QBC)}. We observe that the capacity region defined for a GBC does not carry
over as such to QBC. We show that the optimal decoding scheme for GBC (i.e.,
high SNR user doing successive decoding and low SNR user decoding its message
alone) is not optimal for QBC. We then propose an achievable rate region for
QBC based on two different schemes. We present achievable rate region results
for the case of uniform quantization at the receivers. Next, we investigate the
achievable rate region of two-user GMAC with finite input alphabet and
quantized receiver output. We refer to this channel as {\em quantized multiple
access channel (QMAC)}. We derive expressions for the achievable rate region of
a two-user QMAC. We show that, with finite input alphabet, the achievable rate
region with the commonly used uniform receiver quantizer has a significant loss
compared to the achievable rate region without receiver quantization. We
propose a {\em non-uniform quantizer} which has a significantly larger rate
region compared to what is achieved with a uniform quantizer in QMAC.
|
1102.2787
|
On the Sum Capacity of the Y-Channel
|
cs.IT math.IT
|
A network where three users communicate with each other via a relay is
considered. Users do not receive other users' signals via a direct link, and
thus the relay is essential for their communication. Each user is assumed to
have an individual message to be delivered to each other user. Thus, each user
wants to send two messages and to decode two messages. In general, the transmit
signals of different nodes can be dependent since they can depend on previously
received symbols. We call this case the general case. The sum-capacity is
studied, and upper bounds and lower bounds are given. If all nodes have the
same power, the sum-capacity is characterized to within a gap of 5/2 bits or a
factor of 3 for all values of channel coefficients. This gap is also shown to
approach 3/2 bits as the transmit power increases. Moreover, for the symmetric
case with equal channel coefficients, the gap is shown to be less than 1 bit.
The restricted case is also considered where the transmit signal does not
depend on previously received symbols. In this case, the sum-capacity is
characterized to within a gap of 2 bits or a factor of 3 for all values of
channel coefficients, and approaches 1 bit as the transmit power increases.
|
1102.2794
|
Universal approximation using differentiators and application to
feedback control
|
cs.SY math.OC
|
In this paper, we consider the problems of approximating uncertainties and
feedback control for a class of nonlinear systems without full-known states,
and two approximation methods are proposed: universal approximation using
integral-chain differentiator or extended observer. Comparing to the
approximations by fuzzy system and radial-based-function (RBF) neural networks,
the presented two methods can not only approximate universally the
uncertainties, but also estimate the unknown states. Moreover, the
integral-chain differentiator can restrain noises thoroughly. The theoretical
results are confirmed by computer simulations for feedback control.
|
1102.2797
|
On the Security of Index Coding with Side Information
|
cs.IT math.IT
|
Security aspects of the Index Coding with Side Information (ICSI) problem are
investigated. Building on the results of Bar-Yossef et al. (2006), the
properties of linear index codes are further explored. The notion of weak
security, considered by Bhattad and Narayanan (2005) in the context of network
coding, is generalized to block security. It is shown that the linear index
code based on a matrix $L$, whose column space code $C(L)$ has length $n$,
minimum distance $d$ and dual distance $d^\perp$, is $(d-1-t)$-block secure
(and hence also weakly secure) if the adversary knows in advance $t \leq d-2$
messages, and is completely insecure if the adversary knows in advance more
than $n - d$ messages. Strong security is examined under the conditions that
the adversary: (i) possesses $t$ messages in advance; (ii) eavesdrops at most
$\mu$ transmissions; (iii) corrupts at most $\delta$ transmissions. We prove
that for sufficiently large $q$, an optimal linear index code which is strongly
secure against such an adversary has length $\kappa_q+\mu+2\delta$. Here
$\kappa_q$ is a generalization of the min-rank over $F_q$ of the side
information graph for the ICSI problem in its original formulation in the work
of Bar- Yossef et al.
|
1102.2799
|
Computing the Ball Size of Frequency Permutations under Chebyshev
Distance
|
cs.IT cs.DM math.IT
|
Let $S_n^\lambda$ be the set of all permutations over the multiset
$\{\overbrace{1,...,1}^{\lambda},...,\overbrace{m,...,m}^\lambda\}$ where
$n=m\lambda$. A frequency permutation array (FPA) of minimum distance $d$ is a
subset of $S_n^\lambda$ in which every two elements have distance at least $d$.
FPAs have many applications related to error correcting codes. In coding
theory, the Gilbert-Varshamov bound and the sphere-packing bound are derived
from the size of balls of certain radii. We propose two efficient algorithms
that compute the ball size of frequency permutations under Chebyshev distance.
Both methods extend previous known results. The first one runs in $O({2d\lambda
\choose d\lambda}^{2.376}\log n)$ time and $O({2d\lambda \choose
d\lambda}^{2})$ space. The second one runs in $O({2d\lambda \choose
d\lambda}{d\lambda+\lambda\choose \lambda}\frac{n}{\lambda})$ time and
$O({2d\lambda \choose d\lambda})$ space. For small constants $\lambda$ and $d$,
both are efficient in time and use constant storage space.
|
1102.2808
|
Transductive Ordinal Regression
|
cs.LG
|
Ordinal regression is commonly formulated as a multi-class problem with
ordinal constraints. The challenge of designing accurate classifiers for
ordinal regression generally increases with the number of classes involved, due
to the large number of labeled patterns that are needed. The availability of
ordinal class labels, however, is often costly to calibrate or difficult to
obtain. Unlabeled patterns, on the other hand, often exist in much greater
abundance and are freely available. To take benefits from the abundance of
unlabeled patterns, we present a novel transductive learning paradigm for
ordinal regression in this paper, namely Transductive Ordinal Regression (TOR).
The key challenge of the present study lies in the precise estimation of both
the ordinal class label of the unlabeled data and the decision functions of the
ordinal classes, simultaneously. The core elements of the proposed TOR include
an objective function that caters to several commonly used loss functions
casted in transductive settings, for general ordinal regression. A label
swapping scheme that facilitates a strictly monotonic decrease in the objective
function value is also introduced. Extensive numerical studies on commonly used
benchmark datasets including the real world sentiment prediction problem are
then presented to showcase the characteristics and efficacies of the proposed
transductive ordinal regression. Further, comparisons to recent
state-of-the-art ordinal regression methods demonstrate the introduced
transductive learning paradigm for ordinal regression led to the robust and
improved performance.
|
1102.2816
|
Location-Oblivious Data Transfer with Flying Entangled Qudits
|
quant-ph cs.CR cs.IT math.IT
|
We present a simple and practical quantum protocol involving two mistrustful
agencies in Minkowski space, which allows Alice to transfer data to Bob at a
spacetime location that neither can predict in advance. The location depends on
both Alice's and Bob's actions. The protocol guarantees unconditionally to
Alice that Bob learns the data at a randomly determined location; it guarantees
to Bob that Alice will not learn the transfer location even after the protocol
is complete.
The task implemented, transferring data at a space-time location that remains
hidden from the transferrer, has no precise analogue in non-relativistic
quantum cryptography. It illustrates further the scope for novel cryptographic
applications of relativistic quantum theory.
|
1102.2819
|
Parameter Identification for Markov Models of Biochemical Reactions
|
q-bio.QM cs.CE
|
We propose a numerical technique for parameter inference in Markov models of
biological processes. Based on time-series data of a process we estimate the
kinetic rate constants by maximizing the likelihood of the data. The
computation of the likelihood relies on a dynamic abstraction of the discrete
state space of the Markov model which successfully mitigates the problem of
state space largeness. We compare two variants of our method to
state-of-the-art, recently published methods and demonstrate their usefulness
and efficiency on several case studies from systems biology.
|
1102.2825
|
Algorithmic Aspects of Energy-Delay Tradeoff in Multihop Cooperative
Wireless Networks
|
math.OC cs.DS cs.IT math.IT
|
We consider the problem of energy-efficient transmission in delay constrained
cooperative multihop wireless networks. The combinatorial nature of cooperative
multihop schemes makes it difficult to design efficient polynomial-time
algorithms for deciding which nodes should take part in cooperation, and when
and with what power they should transmit. In this work, we tackle this problem
in memoryless networks with or without delay constraints, i.e., quality of
service guarantee. We analyze a wide class of setups, including unicast,
multicast, and broadcast, and two main cooperative approaches, namely: energy
accumulation (EA) and mutual information accumulation (MIA). We provide a
generalized algorithmic formulation of the problem that encompasses all those
cases. We investigate the similarities and differences of EA and MIA in our
generalized formulation. We prove that the broadcast and multicast problems
are, in general, not only NP hard but also o(log(n)) inapproximable. We break
these problems into three parts: ordering, scheduling and power control, and
propose a novel algorithm that, given an ordering, can optimally solve the
joint power allocation and scheduling problems simultaneously in polynomial
time. We further show empirically that this algorithm used in conjunction with
an ordering derived heuristically using the Dijkstra's shortest path algorithm
yields near-optimal performance in typical settings. For the unicast case, we
prove that although the problem remains NP hard with MIA, it can be solved
optimally and in polynomial time when EA is used. We further use our algorithm
to study numerically the trade-off between delay and power-efficiency in
cooperative broadcast and compare the performance of EA vs MIA as well as the
performance of our cooperative algorithm with a smart noncooperative algorithm
in a broadcast setting.
|
1102.2831
|
The effect of linguistic constraints on the large scale organization of
language
|
cs.CL cs.SI
|
This paper studies the effect of linguistic constraints on the large scale
organization of language. It describes the properties of linguistic networks
built using texts of written language with the words randomized. These
properties are compared to those obtained for a network built over the text in
natural order. It is observed that the "random" networks too exhibit
small-world and scale-free characteristics. They also show a high degree of
clustering. This is indeed a surprising result - one that has not been
addressed adequately in the literature. We hypothesize that many of the network
statistics reported here studied are in fact functions of the distribution of
the underlying data from which the network is built and may not be indicative
of the nature of the concerned network.
|
1102.2836
|
Finite-Memory Prediction as Well as the Empirical Mean
|
cs.IT math.IT
|
The problem of universally predicting an individual continuous sequence using
a deterministic finite-state machine (FSM) is considered. The empirical mean is
used as a reference as it is the constant that fits a given sequence within a
minimal square error. With this reference, a reasonable prediction performance
is the regret, namely the excess square-error over the reference loss, the
empirical variance. The paper analyzes the tradeoff between the number of
states of the universal FSM and the attainable regret. It first studies the
case of a small number of states. A class of machines, denoted Degenerated
Tracking Memory (DTM), is defined and the optimal machine in this class is
shown to be the optimal among all machines for small enough number of states.
Unfortunately, DTM machines become suboptimal as the number of available states
increases. Next, the Exponential Decaying Memory (EDM) machine, previously used
for predicting binary sequences, is considered. While this machine has poorer
performance for small number of states, it achieves a vanishing regret for
large number of states. Following that, an asymptotic lower bound of
O(k^{-2/3}) on the achievable regret of any k-state machine is derived. This
bound is attained asymptotically by the EDM machine. Furthermore, a new
machine, denoted the Enhanced Exponential Decaying Memory machine, is shown to
outperform the EDM machine for any number of states.
|
1102.2837
|
Efficient Promotion Strategies in Hierarchical Organizations
|
physics.soc-ph cs.SI
|
The Peter principle has been recently investigated by means of an agent-based
simulation and its validity has been numerically corroborated. It has been
confirmed that, within certain conditions, it can really influence in a
negative way the efficiency of a pyramidal organization adopting meritocratic
promotions. It was also found that, in order to bypass these effects,
alternative promotion strategies should be adopted, as for example a random
selection choice. In this paper, within the same line of research, we study
promotion strategies in a more realistic hierarchical and modular organization
and we show the robustness of our previous results, extending their validity to
a more general context. We discuss also why the adoption of these strategies
could be useful for real organizations.
|
1102.2840
|
Spectrum Sensing Based on Blindly Learned Signal Feature
|
cs.IT math.IT
|
Spectrum sensing is the major challenge in the cognitive radio (CR). We
propose to learn local feature and use it as the prior knowledge to improve the
detection performance. We define the local feature as the leading eigenvector
derived from the received signal samples. A feature learning algorithm (FLA) is
proposed to learn the feature blindly. Then, with local feature as the prior
knowledge, we propose the feature template matching algorithm (FTM) for
spectrum sensing. We use the discrete Karhunen--Lo{\`e}ve transform (DKLT) to
show that such a feature is robust against noise and has maximum effective
signal-to-noise ratio (SNR). Captured real-world data shows that the learned
feature is very stable over time. It is almost unchanged in 25 seconds. Then,
we test the detection performance of the FTM in very low SNR. Simulation
results show that the FTM is about 2 dB better than the blind algorithms, and
the FTM does not have the noise uncertainty problem.
|
1102.2856
|
Spatially Coupled Codes over the Multiple Access Channel
|
cs.IT math.IT
|
We consider spatially coupled code ensembles over a multiple access channel.
Convolutional LDPC ensembles are one instance of spatially coupled codes. It
was shown recently that, for transmission over the binary erasure channel, this
coupling of individual code ensembles has the effect of increasing the belief
propagation threshold of the coupled ensembles to the maximum a-posteriori
threshold of the underlying ensemble. In this sense, spatially coupled codes
were shown to be capacity achieving. It was observed, empirically, that these
codes are universal in the sense that they achieve performance close to the
Shannon threshold for any general binary-input memoryless symmetric channels.
In this work we provide further evidence of the threshold saturation
phenomena when transmitting over a class of multiple access channel. We show,
by density evolution analysis and EXIT curves, that the belief propagation
threshold of the coupled ensembles is very close to the ultimate Shannon limit.
|
1102.2868
|
Interference Networks with Point-to-Point Codes
|
cs.IT math.IT math.PR
|
The paper establishes the capacity region of the Gaussian interference
channel with many transmitter-receiver pairs constrained to use point-to-point
codes. The capacity region is shown to be strictly larger in general than the
achievable rate regions when treating interference as noise, using successive
interference cancellation decoding, and using joint decoding. The gains in
coverage and achievable rate using the optimal decoder are analyzed in terms of
ensemble averages using stochastic geometry. In a spatial network where the
nodes are distributed according to a Poisson point process and the channel path
loss exponent is $\beta > 2$, it is shown that the density of users that can be
supported by treating interference as noise can scale no faster than
$B^{2/\beta}$ as the bandwidth $B$ grows, while the density of users can scale
linearly with $B$ under optimal decoding.
|
1102.2881
|
Modified Orthogonal Matching Pursuit Algorithm for Cognitive Radio
Wideband Spectrum Sensing
|
cs.IT math.IT
|
Sampling rate is the bottleneck for spectrum sensing over multi-GHz
bandwidth. Recent progress in compressed sensing (CS) initialized several
sub-Nyquist rate approaches to overcome the problem. However, efforts to design
CS reconstruction algorithms for wideband spectrum sensing are very limited. It
is possible to further reduce the sampling rate requirement and improve
reconstruction performance via algorithms considering prior knowledge of
cognitive radio spectrum usages. In this paper, we group the usages of
cognitive radio spectrum into three categories and propose a modified
orthogonal matching pursuit (OMP) algorithm for wideband spectrum sensing.
Simulation results show that this modified OMP algorithm outperforms two
modified basis pursuit de-noising (BPDN) algorithms in terms of reconstruction
performance and computation time.
|
1102.2890
|
Some Notes on Quantum Information Theory and Emerging Computing
Technologies
|
cs.IT math.IT quant-ph
|
It is considered an interdependence of the theory of quantum computing and
some perspective information technologies. A couple of illustrative and useful
examples are discussed. The reversible computing from very beginning had the
serious impact on the design of quantum computers and it is revisited first.
Some applications of ternary circuits are also quite instructive and it may be
useful in the quantum information theory.
|
1102.2891
|
Usage Bibliometrics
|
cs.DL astro-ph.IM cs.IR physics.soc-ph
|
Scholarly usage data provides unique opportunities to address the known
shortcomings of citation analysis. However, the collection, processing and
analysis of usage data remains an area of active research. This article
provides a review of the state-of-the-art in usage-based informetric, i.e. the
use of usage data to study the scholarly process.
|
1102.2904
|
The Asymptotic Limits of Interference in Multicell Networks with Channel
Aware Scheduling
|
cs.IT math.IT
|
Interference is emerging as a fundamental bottleneck in many important
wireless communication scenarios, including dense cellular networks and
cognitive networks with spectrum sharing by multiple service providers.
Although multipleantenna (MIMO) signal processing is known to offer useful
degrees of freedom to cancel interference, extreme-value theoretic analysis
recently showed that, even in the absence of MIMO processing, the scaling law
of the capacity in the number of users for a multi-cell network with and
without inter-cell interference was asymptotically identical provided a simple
signal to noise and interference ratio (SINR) maximizing scheduler is
exploited. This suggests that scheduling can help reduce inter-cell
interference substantially, thus possibly limiting the need for
multiple-antenna processing. However, the convergence limits of interference
after scheduling in a multi-cell setting are not yet identified. In this paper1
we analyze such limits theoretically. We consider channel statistics under
Rayleigh fading with equal path loss for all users or with unequal path loss.
We uncover two surprisingly different behaviors for such systems. For the equal
path loss case, we show that scheduling alone can cause the residual
interference to converge to zero for large number of users. With unequal path
loss however, the interference are shown to converge in average to a nonzero
constant. Simulations back our findings.
|
1102.2928
|
Density Evolution Analysis of Node-Based Verification-Based Algorithms
in Compressed Sensing
|
cs.IT math.IT
|
In this paper, we present a new approach for the analysis of iterative
node-based verification-based (NB-VB) recovery algorithms in the context of
compressive sensing. These algorithms are particularly interesting due to their
low complexity (linear in the signal dimension $n$). The asymptotic analysis
predicts the fraction of unverified signal elements at each iteration $\ell$ in
the asymptotic regime where $n \rightarrow \infty$. The analysis is similar in
nature to the well-known density evolution technique commonly used to analyze
iterative decoding algorithms. To perform the analysis, a message-passing
interpretation of NB-VB algorithms is provided. This interpretation lacks the
extrinsic nature of standard message-passing algorithms to which density
evolution is usually applied. This requires a number of non-trivial
modifications in the analysis. The analysis tracks the average performance of
the recovery algorithms over the ensembles of input signals and sensing
matrices as a function of $\ell$. Concentration results are devised to
demonstrate that the performance of the recovery algorithms applied to any
choice of the input signal over any realization of the sensing matrix follows
the deterministic results of the analysis closely. Simulation results are also
provided which demonstrate that the proposed asymptotic analysis matches the
performance of recovery algorithms for large but finite values of $n$. Compared
to the existing technique for the analysis of NB-VB algorithms, which is based
on numerically solving a large system of coupled differential equations, the
proposed method is much simpler and more accurate.
|
1102.2933
|
A FEniCS-Based Programming Framework for Modeling Turbulent Flow by the
Reynolds-Averaged Navier-Stokes Equations
|
cs.CE physics.comp-ph physics.flu-dyn
|
Finding an appropriate turbulence model for a given flow case usually calls
for extensive experimentation with both models and numerical solution methods.
This work presents the design and implementation of a flexible, programmable
software framework for assisting with numerical experiments in computational
turbulence. The framework targets Reynolds-averaged Navier-Stokes models,
discretized by finite element methods. The novel implementation makes use of
Python and the FEniCS package, the combination of which leads to compact and
reusable code, where model- and solver-specific code resemble closely the
mathematical formulation of equations and algorithms. The presented ideas and
programming techniques are also applicable to other fields that involve systems
of nonlinear partial differential equations. We demonstrate the framework in
two applications and investigate the impact of various linearizations on the
convergence properties of nonlinear solvers for a Reynolds-averaged
Navier-Stokes model.
|
1102.2935
|
Fundamental Limits of Infinite Constellations in MIMO Fading Channels
|
cs.IT math.IT
|
The fundamental and natural connection between the infinite constellation
(IC) dimension and the best diversity order it can achieve is investigated in
this paper. In the first part of this work we develop an upper bound on the
diversity order of IC's for any dimension and any number of transmit and
receive antennas. By choosing the right dimensions, we prove in the second part
of this work that IC's in general and lattices in particular can achieve the
optimal diversity-multiplexing tradeoff of finite constellations. This work
gives a framework for designing lattices for multiple-antenna channels using
lattice decoding.
|
1102.2936
|
Decoding by Embedding: Correct Decoding Radius and DMT Optimality
|
cs.IT math.IT
|
The closest vector problem (CVP) and shortest (nonzero) vector problem (SVP)
are the core algorithmic problems on Euclidean lattices. They are central to
the applications of lattices in many problems of communications and
cryptography. Kannan's \emph{embedding technique} is a powerful technique for
solving the approximate CVP, yet its remarkable practical performance is not
well understood. In this paper, the embedding technique is analyzed from a
\emph{bounded distance decoding} (BDD) viewpoint. We present two complementary
analyses of the embedding technique: We establish a reduction from BDD to
Hermite SVP (via unique SVP), which can be used along with any Hermite SVP
solver (including, among others, the Lenstra, Lenstra and Lov\'asz (LLL)
algorithm), and show that, in the special case of LLL, it performs at least as
well as Babai's nearest plane algorithm (LLL-aided SIC). The former analysis
helps to explain the folklore practical observation that unique SVP is easier
than standard approximate SVP. It is proven that when the LLL algorithm is
employed, the embedding technique can solve the CVP provided that the noise
norm is smaller than a decoding radius $\lambda_1/(2\gamma)$, where $\lambda_1$
is the minimum distance of the lattice, and $\gamma \approx O(2^{n/4})$. This
substantially improves the previously best known correct decoding bound $\gamma
\approx {O}(2^{n})$. Focusing on the applications of BDD to decoding of
multiple-input multiple-output (MIMO) systems, we also prove that BDD of the
regularized lattice is optimal in terms of the diversity-multiplexing gain
tradeoff (DMT), and propose practical variants of embedding decoding which
require no knowledge of the minimum distance of the lattice and/or further
improve the error performance.
|
1102.2939
|
On the Decoding Complexity of Cyclic Codes Up to the BCH Bound
|
cs.IT math.IT
|
The standard algebraic decoding algorithm of cyclic codes $[n,k,d]$ up to the
BCH bound $t$ is very efficient and practical for relatively small $n$ while it
becomes unpractical for large $n$ as its computational complexity is $O(nt)$.
Aim of this paper is to show how to make this algebraic decoding
computationally more efficient: in the case of binary codes, for example, the
complexity of the syndrome computation drops from $O(nt)$ to $O(t\sqrt n)$, and
that of the error location from $O(nt)$ to at most $\max \{O(t\sqrt n),
O(t^2\log(t)\log(n))\}$.
|
1102.2946
|
A Large Deviations Result for Aggregation of Independent Noisy
Observations
|
cs.IT math.IT
|
Sensing and aggregation of noisy observations should not be considered as
separate issues. The quality of collective estimation involves a difficult
tradeoff between sensing quality which increases by increasing the number of
sensors, and aggregation quality which typically decreases if the number of
sensors is too large. We examine a strategy for optimal aggregation for an
ensemble of independent sensors with constrained system capacity. We show that
in the large capacity limit larger scale aggregation always outperforms smaller
scale aggregation at higher noise levels, while below a critical value of
noise, there exist moderate scale aggregation levels at which optimal
estimation is realized.
|
1102.2950
|
Kron Reduction of Graphs with Applications to Electrical Networks
|
math.CO cs.DM cs.SY math-ph math.MP math.OC
|
Consider a weighted and undirected graph, possibly with self-loops, and its
corresponding Laplacian matrix, possibly augmented with additional diagonal
elements corresponding to the self-loops. The Kron reduction of this graph is
again a graph whose Laplacian matrix is obtained by the Schur complement of the
original Laplacian matrix with respect to a subset of nodes. The Kron reduction
process is ubiquitous in classic circuit theory and in related disciplines such
as electrical impedance tomography, smart grid monitoring, transient stability
assessment in power networks, or analysis and simulation of induction motors
and power electronics. More general applications of Kron reduction occur in
sparse matrix algorithms, multi-grid solvers, finite--element analysis, and
Markov chains. The Schur complement of a Laplacian matrix and related concepts
have also been studied under different names and as purely theoretic problems
in the literature on linear algebra. In this paper we propose a general
graph-theoretic framework for Kron reduction that leads to novel and deep
insights both on the mathematical and the physical side. We show the
applicability of our framework to various practical problem setups arising in
engineering applications and computation. Furthermore, we provide a
comprehensive and detailed graph-theoretic analysis of the Kron reduction
process encompassing topological, algebraic, spectral, resistive, and
sensitivity analyses. Throughout our theoretic elaborations we especially
emphasize the practical applicability of our results.
|
1102.2955
|
Quantum interference channels
|
quant-ph cs.IT math.IT
|
The discrete memoryless interference channel is modelled as a conditional
probability distribution with two outputs depending on two inputs and has
widespread applications in practical communication scenarios. In this paper, we
introduce and study the quantum interference channel, a generalization of a
two-input, two-output memoryless channel to the setting of quantum Shannon
theory. We discuss three different coding strategies and obtain corresponding
achievable rate regions for quantum interference channels. We calculate the
capacity regions in the special cases of "very strong" and "strong"
interference. The achievability proof in the case of "strong" interference
exploits a novel quantum simultaneous decoder for two-sender quantum multiple
access channels. We formulate a conjecture regarding the existence of a quantum
simultaneous decoder in the three-sender case and use it to state the rates
achievable by a quantum Han-Kobayashi strategy.
|
1102.2969
|
Efficient and scalable geometric hashing method for searching protein 3D
structures
|
cs.DB q-bio.QM
|
As the structural databases continue to expand, efficient methods are
required to search similar structures of the query structure from the database.
There are many previous works about comparing protein 3D structures and
scanning the database with a query structure. However, they generally have
limitations on practical use because of large computational and storage
requirements.
We propose two new types of queries for searching similar sub-structures on
the structural database: LSPM (Local Spatial Pattern Matching) and RLSPM
(Reverse LSPM). Between two types of queries, we focus on RLSPM problem,
because it is more practical and general than LSPM. As a naive algorithm, we
adopt geometric hashing techniques to RLSPM problem and then propose our
proposed algorithm which improves the baseline algorithm to deal with
large-scale data and provide an efficient matching algorithm. We employ the
sub-sampling and Z-ordering to reduce the storage requirement and execution
time, respectively. We conduct our experiments to show the correctness and
reliability of the proposed method. Our experiment shows that the true positive
rate is at least 0.8 using the reliability measure.
|
1102.2975
|
Decentralized Restless Bandit with Multiple Players and Unknown Dynamics
|
math.OC cs.LG cs.SY math.PR
|
We consider decentralized restless multi-armed bandit problems with unknown
dynamics and multiple players. The reward state of each arm transits according
to an unknown Markovian rule when it is played and evolves according to an
arbitrary unknown random process when it is passive. Players activating the
same arm at the same time collide and suffer from reward loss. The objective is
to maximize the long-term reward by designing a decentralized arm selection
policy to address unknown reward models and collisions among players. A
decentralized policy is constructed that achieves a regret with logarithmic
order when an arbitrary nontrivial bound on certain system parameters is known.
When no knowledge about the system is available, we extend the policy to
achieve a regret arbitrarily close to the logarithmic order. The result finds
applications in communication networks, financial investment, and industrial
engineering.
|
1102.2984
|
Hybrid Model for Solving Multi-Objective Problems Using Evolutionary
Algorithm and Tabu Search
|
cs.AI
|
This paper presents a new multi-objective hybrid model that makes cooperation
between the strength of research of neighborhood methods presented by the tabu
search (TS) and the important exploration capacity of evolutionary algorithm.
This model was implemented and tested in benchmark functions (ZDT1, ZDT2, and
ZDT3), using a network of computers.
|
1102.2986
|
Sidon Sequences and Doubly Periodic Two-Dimensional Synchronization
Patterns
|
cs.IT math.IT
|
Sidon sequences and their generalizations have found during the years and
especially recently various applications in coding theory. One of the most
important applications of these sequences is in the connection of
synchronization patterns. A few constructions of two-dimensional
synchronization patterns are based on these sequences. In this paper we present
sufficient conditions that a two-dimensional synchronization pattern can be
transformed into a Sidon sequence. We also present a new construction for Sidon
sequences over an alphabet of size q(q-1), where q is a power of a prime.
|
1102.3002
|
Secure Multiplex Network Coding
|
cs.IT cs.CR math.IT
|
In the secure network coding for multicasting, there is loss of information
rate due to inclusion of random bits at the source node. We show a method to
eliminate that loss of information rate by using multiple statistically
independent messages to be kept secret from an eavesdropper. The proposed
scheme is an adaptation of Yamamoto et al.'s secure multiplex coding to the
secure network coding.
|
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