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1102.3029
|
Analysis of multi-stage open shop processing systems
|
cs.DS cs.SY math.OC
|
We study algorithmic problems in multi-stage open shop processing systems
that are centered around reachability and deadlock detection questions. We
characterize safe and unsafe system states. We show that it is easy to
recognize system states that can be reached from the initial state (where the
system is empty), but that in general it is hard to decide whether one given
system state is reachable from another given system state. We show that the
problem of identifying reachable deadlock states is hard in general open shop
systems, but is easy in the special case where no job needs processing on more
than two machines (by linear programming and matching theory), and in the
special case where all machines have capacity one (by graph-theoretic
arguments).
|
1102.3044
|
The Multiplexing Gain of a Two-cell MIMO Channel with Unequal CSI
|
cs.IT math.IT
|
In this work, the joint precoding across two distant transmitters (TXs),
sharing the knowledge of the data symbols to be transmitted, to two receivers
(RXs), each equipped with one antenna, is discussed. We consider a distributed
channel state information (CSI) configuration where each TX has its own local
estimate of the channel and no communication is possible between the TXs. Based
on the distributed CSI configuration, we introduce a concept of distributed
MIMO precoding. We focus on the high signal-to-noise ratio (SNR) regime such
that the two TXs aim at designing a precoding matrix to cancel the
interference. Building on the study of the multiple antenna broadcast channel,
we obtain the following key results: We derive the multiplexing gain (MG) as a
function of the scaling in the SNR of the number of bits quantizing at each TX
the channel to a given RX. Particularly, we show that the conventional Zero
Forcing precoder is not MG maximizing, and we provide a precoding scheme
optimal in terms of MG. Beyond the established MG optimality, simulations show
that the proposed precoding schemes achieve better performances at intermediate
SNR than known linear precoders.
|
1102.3056
|
A Phenomenological Study on Threshold Improvement via Spatial Coupling
|
cs.IT math.IT
|
Kudekar et al. proved an interesting result in low-density parity-check
(LDPC) convolutional codes: The belief-propagation (BP) threshold is boosted to
the maximum-a-posteriori (MAP) threshold by spatial coupling. Furthermore, the
authors showed that the BP threshold for code-division multiple-access (CDMA)
systems is improved up to the optimal one via spatial coupling. In this letter,
a phenomenological model for elucidating the essence of these phenomenon,
called threshold improvement, is proposed. The main result implies that
threshold improvement occurs for spatially-coupled general graphical models.
|
1102.3061
|
Improvement of BP-Based CDMA Multiuser Detection by Spatial Coupling
|
cs.IT math.IT
|
Kudekar et al. proved that the belief-propagation (BP) threshold for
low-density parity-check codes can be boosted up to the maximum-a-posteriori
(MAP) threshold by spatial coupling. In this paper, spatial coupling is applied
to randomly-spread code-division multiple-access (CDMA) systems in order to
improve the performance of BP-based multiuser detection (MUD).
Spatially-coupled CDMA systems can be regarded as multi-code CDMA systems with
two transmission phases. The large-system analysis shows that spatial coupling
can improve the BP performance, while there is a gap between the BP performance
and the individually-optimal (IO) performance.
|
1102.3063
|
Adiabatic control of the Schr\"odinger equation via conical
intersections of the eigenvalues
|
math.OC cs.SY
|
In this paper we present a constructive method to control the bilinear
Schr\"odinger equation via two controls. The method is based on adiabatic
techniques and works if the spectrum of the Hamiltonian admits eigenvalue
intersections, and if the latter are conical (as it happens generically). We
provide sharp estimates of the relation between the error and the
controllability time.
|
1102.3067
|
Investigating the topology of interacting networks - Theory and
application to coupled climate subnetworks
|
physics.data-an cs.SI physics.ao-ph physics.soc-ph
|
Network theory provides various tools for investigating the structural or
functional topology of many complex systems found in nature, technology and
society. Nevertheless, it has recently been realised that a considerable number
of systems of interest should be treated, more appropriately, as interacting
networks or networks of networks. Here we introduce a novel graph-theoretical
framework for studying the interaction structure between subnetworks embedded
within a complex network of networks. This framework allows us to quantify the
structural role of single vertices or whole subnetworks with respect to the
interaction of a pair of subnetworks on local, mesoscopic and global
topological scales.
Climate networks have recently been shown to be a powerful tool for the
analysis of climatological data. Applying the general framework for studying
interacting networks, we introduce coupled climate subnetworks to represent and
investigate the topology of statistical relationships between the fields of
distinct climatological variables. Using coupled climate subnetworks to
investigate the terrestrial atmosphere's three-dimensional geopotential height
field uncovers known as well as interesting novel features of the atmosphere's
vertical stratification and general circulation. Specifically, the new measure
"cross-betweenness" identifies regions which are particularly important for
mediating vertical wind field interactions. The promising results obtained by
following the coupled climate subnetwork approach present a first step towards
an improved understanding of the Earth system and its complex interacting
components from a network perspective.
|
1102.3080
|
Covering Point Patterns
|
cs.IT math.IT
|
An encoder observes a point pattern---a finite number of points in the
interval $[0,T]$---which is to be described to a reconstructor using bits.
Based on these bits, the reconstructor wishes to select a subset of $[0,T]$
that contains all the points in the pattern. It is shown that, if the point
pattern is produced by a homogeneous Poisson process of intensity $\lambda$,
and if the reconstructor is restricted to select a subset of average Lebesgue
measure not exceeding $DT$, then, as $T$ tends to infinity, the minimum number
of bits per second needed by the encoder is $-\lambda\log D$. It is also shown
that, as $T$ tends to infinity, any point pattern on $[0,T]$ containing no more
than $\lambda T$ points can be successfully described using $-\lambda \log D$
bits per second in this sense. Finally, a Wyner-Ziv version of this problem is
considered where some of the points in the pattern are known to the
reconstructor.
|
1102.3082
|
Hash-and-Forward Relaying for Two-Way Relay Channel
|
cs.IT math.IT
|
This paper considers a communication network comprised of two nodes, which
have no mutual direct communication links, communicating two-way with the aid
of a common relay node (RN), also known as separated two-way relay (TWR)
channel.
We first recall a cut-set outer bound for the set of rates in the context of
this network topology assuming full-duplex transmission capabilities. Then, we
derive a new achievable rate region based on hash-and-forward (HF) relaying
where the RN does not attempt to decode but instead hashes its received signal,
and show that under certain channel conditions it coincides with Shannon's
inner-bound for the two-way channel [1]. Moreover, for binary adder TWR channel
with additive noise at the nodes and the RN we provide a detailed capacity
achieving coding scheme based on structure codes.
|
1102.3120
|
Interference Two-Way Relay Channel with Three End-nodes
|
cs.IT math.IT
|
In this paper, we study a communication system consisting of three end-nodes,
e.g. a single transceiver base station (BS), one transmitting and one receiving
user equipments (UEs), and a common two-way relay node (RN) wherein the
full-duplex BS transmits to the receiving UE in downlink direction and receives
from the transmitting UE in uplink direction with the help of the intermediate
full-duplex RN. We call this system model as interference two-way relay channel
(ITWRC) with three end-nodes. Information theoretic bounds corresponding this
system model are derived and analyzed so as to better understand the potentials
of exploiting RN in future communication systems. Specifically, achievable rate
regions corresponding to decode-and-forward (DF) relaying with and without rate
splitting, and partial-DF and compress-and-forward (pDF+CF) relaying strategies
are derived.
|
1102.3126
|
Reduced-Complexity Collaborative Decoding of Interleaved Reed-Solomon
and Gabidulin Codes
|
cs.IT math.IT
|
An alternative method for collaborative decoding of interleaved Reed-Solomon
codes as well as Gabidulin codes for the case of high interleaving degree is
proposed. As an example of application, simulation results are presented for a
concatenated coding scheme using polar codes as inner codes.
|
1102.3127
|
On the Cognitive Interference Channel with Unidirectional Destination
Cooperation
|
cs.IT math.IT
|
The cognitive interference channel with unidirectional destination
cooperation (CIFC-UDC) is a cognitive interference channel (CIFC) where the
cognitive (secondary) destination not only decodes the information sent from
its sending dual but also helps enhance the communication of the primary user.
This channel model is an extension of the original CIFC to achieve a win-win
solution under the coexistence condition. From an information-theoretic
perspective, the CIFC-UDC comprises a broadcast channel (BC), a relay channel
(RC) and a partially cooperative relay broadcast channel (PCRBC), and can be
degraded to any one of them. Our main result is the establishment of a new
unified achieva-ble rate region for the CIFC-UDC which is the largest known to
date and can be explicitly shown to include the previous result proposed by Chu
and the largest known rate regions for the BC, the RC and the PCRBC. In
addition, an interesting viewpoint on the unidirectional destination
cooperation in the CIFC-UDC is discussed: to enable the decoder of the primary
user to perform interference mitigation can be considered as a complementary
idea to the interference mitigation via Gel'fand-Pinsker precod-ing in the CIFC
proposed by Devroye et al. Henceforth, by com-bing these two ideas, the
interferences caused at both the desti-nations can be alleviated. Lastly, an
outer bound is presented and proved to be tight for a class of the CIFC-UDC,
resulting in the characterization of the capacity region for this class.
|
1102.3129
|
Automated Complexity Analysis Based on the Dependency Pair Method
|
cs.LO cs.AI cs.CC cs.PL
|
This article is concerned with automated complexity analysis of term rewrite
systems. Since these systems underlie much of declarative programming, time
complexity of functions defined by rewrite systems is of particular interest.
Among other results, we present a variant of the dependency pair method for
analysing runtime complexities of term rewrite systems automatically. The
established results significantly extent previously known techniques: we give
examples of rewrite systems subject to our methods that could previously not
been analysed automatically. Furthermore, the techniques have been implemented
in the Tyrolean Complexity Tool. We provide ample numerical data for assessing
the viability of the method.
|
1102.3132
|
Connection between Annealed Free Energy and Belief Propagation on Random
Factor Graph Ensembles
|
cs.IT math.IT
|
Recently, Vontobel showed the relationship between Bethe free energy and
annealed free energy for protograph factor graph ensembles. In this paper,
annealed free energy of any random regular, irregular and Poisson factor graph
ensembles are connected to Bethe free energy. The annealed free energy is
expressed as the solution of maximization problem whose stationary condition
equations coincide with equations of belief propagation since the contribution
to partition function of particular type of variable and factor nodes has
similar form of minus Bethe free energy. It gives simple derivation of replica
symmetric solution. As consequence, it is shown that on replica symmetric
ansatz, replica symmetric solution and annealed free energy are equal for
regular ensemble.
|
1102.3140
|
Capacity Region of $K$-User Discrete Memoryless Interference Channels
with a Mixed Strong-Very Strong Interference
|
cs.IT math.IT
|
The capacity region of the 3-user Gaussian Interference Channel (GIC) with
mixed strong-very strong interference was established in \cite{ChS}. The mixed
strong-very strong interference conditions considered in \cite{ChS} correspond
to the case where, at each receiver, one of the interfering signals is strong
and the other is very strong. In this paper, we derive the capacity region of
$K$-user $(K\geq 3)$ Discrete Memoryless Interference Channels (DMICs) with a
mixed strong-very strong interference. This corresponds to the case where, at
each receiver one of the interfering signals is strong and the other $(K-2)$
interfering signals are very strong. This includes, as a special case, the
3-user DMIC with mixed strong-very strong interference. The proof is
specialized to the 3-user GIC case and hence an alternative simpler derivation
for the capacity region of the 3-user GIC with mixed strong-very strong
interference is provided.
|
1102.3162
|
Network Coding: Is zero error always possible?
|
cs.IT math.IT
|
In this work we study zero vs. epsilon-error capacity in network coding
instances. For multicast network coding it is well known that all rates that
can be delivered with arbitrarily small error probability can also be delivered
with zero error probability; that is, the epsilon-error multicast capacity
region and zero-error multicast capacity region are identical. For general
network coding instances in which all sources originate at the same source
node, Chan and Grant recently showed [ISIT 2010] that, again, epsilon-error
communication has no rate advantage over zero-error communication.
We start by revisiting the setting of co-located sources, where we present an
alternative proof to that given by Chan and Grant. While the new proof is based
on similar core ideas, our constructive strategy complements the previous
argument.We then extend our results to the setting of index coding, which is a
special and representative form of network coding that encapsulates the "source
coding with side information" problem. Finally, we consider the "edge removal"
problem (recently studied by Jalali, Effros, and Ho in [Allerton 2010] and [ITA
2011]) that aims to quantify the loss in capacity associated with removing a
single edge from a given network. Using our proof for co-located sources, we
tie the "zero vs. epsilon-error" problem in general network coding instances
with the "edge removal" problem. Loosely speaking, we show that the two problem
are equivalent.
|
1102.3165
|
An Approximation Algorithm for Computing Shortest Paths in Weighted 3-d
Domains
|
cs.CG cs.DS cs.GR cs.RO
|
We present the first polynomial time approximation algorithm for computing
shortest paths in weighted three-dimensional domains. Given a polyhedral domain
$\D$, consisting of $n$ tetrahedra with positive weights, and a real number
$\eps\in(0,1)$, our algorithm constructs paths in $\D$ from a fixed source
vertex to all vertices of $\D$, whose costs are at most $1+\eps$ times the
costs of (weighted) shortest paths, in
$O(\C(\D)\frac{n}{\eps^{2.5}}\log\frac{n}{\eps}\log^3\frac{1}{\eps})$ time,
where $\C(\D)$ is a geometric parameter related to the aspect ratios of
tetrahedra. The efficiency of the proposed algorithm is based on an in-depth
study of the local behavior of geodesic paths and additive Voronoi diagrams in
weighted three-dimensional domains, which are of independent interest. The
paper extends the results of Aleksandrov, Maheshwari and Sack [JACM 2005] to
three dimensions.
|
1102.3167
|
A Complete Characterization of Irreducible Cyclic Orbit Codes
|
cs.IT math.IT
|
We give a complete list of orbit codes that are generated by an irreducible
cyclic group, i.e. an irreducible group having one generator. We derive some of
the basic properties of these codes such as the cardinality and the minimum
distance.
|
1102.3176
|
Selecting the rank of truncated SVD by Maximum Approximation Capacity
|
cs.IT cs.LG math.IT stat.ML
|
Truncated Singular Value Decomposition (SVD) calculates the closest rank-$k$
approximation of a given input matrix. Selecting the appropriate rank $k$
defines a critical model order choice in most applications of SVD. To obtain a
principled cut-off criterion for the spectrum, we convert the underlying
optimization problem into a noisy channel coding problem. The optimal
approximation capacity of this channel controls the appropriate strength of
regularization to suppress noise. In simulation experiments, this information
theoretic method to determine the optimal rank competes with state-of-the art
model selection techniques.
|
1102.3181
|
Spatially Coupled Quasi-Cyclic Quantum LDPC Codes
|
cs.IT math.IT quant-ph
|
We face the following dilemma for designing low-density parity-check codes
(LDPC) for quantum error correction. 1) The row weights of parity-check should
be large: The minimum distances are bounded above by the minimum row weights of
parity-check matrices of constituent classical codes. Small minimum distance
tends to result in poor decoding performance at the error-floor region. 2) The
row weights of parity-check matrices should not be large: The sum-product
decoding performance at the water-fall region is degraded as the row weight
increases. Recently, Kudekar et al. showed spatially-coupled (SC) LDPC codes
exhibit capacity-achieving performance for classical channels. SC LDPC codes
have both large row weight and capacity-achieving error-floor and water-fall
performance. In this paper, we design SC LDPC-CSS (Calderbank, Shor and Steane)
codes for quantum error correction over the depolarizing channels.
|
1102.3204
|
One Packet Suffices - Highly Efficient Packetized Network Coding With
Finite Memory
|
cs.IT cs.DS math.IT
|
Random Linear Network Coding (RLNC) has emerged as a powerful tool for robust
high-throughput multicast. Projection analysis - a recently introduced
technique - shows that the distributed packetized RLNC protocol achieves
(order) optimal and perfectly pipelined information dissemination in many
settings. In the original approach to RNLC intermediate nodes code together all
available information. This requires intermediate nodes to keep considerable
data available for coding. Moreover, it results in a coding complexity that
grows linearly with the size of this data. While this has been identified as a
problem, approaches that combine queuing theory and network coding have
heretofore not provided a succinct representation of the memory needs of
network coding at intermediates nodes.
This paper shows the surprising result that, in all settings with a
continuous stream of data, network coding continues to perform optimally even
if only one packet per node is kept in active memory and used for computations.
This leads to an extremely simple RLNC protocol variant with drastically
reduced requirements on computational and memory resources. By extending the
projection analysis, we show that in all settings in which the RLNC protocol
was proven to be optimal its finite memory variant performs equally well. In
the same way as the original projection analysis, our technique applies in a
wide variety of network models, including highly dynamic topologies that can
change completely at any time in an adversarial fashion.
|
1102.3214
|
LQG Control Approach to Gaussian Broadcast Channels with Feedback
|
cs.IT math.IT math.OC
|
A code for communication over the k-receiver additive white Gaussian noise
broadcast channel with feedback is presented and analyzed using tools from the
theory of linear quadratic Gaussian optimal control. It is shown that the
performance of this code depends on the noise correlation at the receivers and
it is related to the solution of a discrete algebraic Riccati equation. For the
case of independent noises, the sum rate achieved by the proposed code,
satisfying average power constraint P, is characterized as 1/2 log (1+P*phi),
where the coefficient "phi" in the interval [1,k] quantifies the power gain due
to the presence of feedback. When specialized to the case of two receivers,
this includes a previous result by Elia and strictly improves upon the code of
Ozarow and Leung. When the noises are correlated, the pre-log of the
sum-capacity of the broadcast channel with feedback can be strictly greater
than one. It is established that for all noise covariance matrices of rank r
the pre-log of the sum capacity is at most k-r+1 and, conversely, there exists
a noise covariance matrix of rank r for which the proposed code achieves this
upper bound. This generalizes a previous result by Gastpar and Wigger for the
two-receiver broadcast channel.
|
1102.3216
|
The Two-User Gaussian Fading Broadcast Channel
|
cs.IT math.IT
|
This paper presents outerbounds for the two-user Gaussian fading broadcast
channel. These outerbounds are based on Costa's entropy power inequality
(Costa-EPI) and are formulated mathematically as a feasibility problem. For
classes of the two-user Gaussian fading broadcast channel where the outerbound
is found to have a feasible solution, we find conditions under which a suitable
inner and outer bound meet. For all such cases, this paper provides a partial
characterization of the capacity region of the Gaussian two-user fading
broadcast channel.
|
1102.3220
|
A signal recovery algorithm for sparse matrix based compressed sensing
|
cs.IT cond-mat.dis-nn math.IT
|
We have developed an approximate signal recovery algorithm with low
computational cost for compressed sensing on the basis of randomly constructed
sparse measurement matrices. The law of large numbers and the central limit
theorem suggest that the developed algorithm saturates the Donoho-Tanner weak
threshold for the perfect recovery when the matrix becomes as dense as the
signal size $N$ and the number of measurements $M$ tends to infinity keep
$\alpha=M/N \sim O(1)$, which is supported by extensive numerical experiments.
Even when the numbers of non-zero entries per column/row in the measurement
matrices are limited to $O(1)$, numerical experiments indicate that the
algorithm can still typically recover the original signal perfectly with an
$O(N)$ computational cost per update as well if the density $\rho$ of non-zero
entries of the signal is lower than a certain critical value $\rho_{\rm
th}(\alpha)$ as $N,M \to \infty$.
|
1102.3225
|
Capacity to within 3 bits for a class of Gaussian Interference Channels
with a Cognitive Relay
|
cs.IT math.IT
|
The InterFerence Channel with a Cognitive Relay (IFC-CR) consists of a
classical two-user interference channel in which the two independent messages
are also non-causally known at a cognitive relay node. In this work a special
class of IFC-CRs in which the sources do not create interference at the
non-intended destinations is analyzed. This special model results in a channel
with two non-interfering point-to-point channels whose transmission is aided by
an in-band cognitive relay, which is thus referred to as the Parallel Channel
with a Cognitive Relay (PC-CR). We determine the capacity of the PC-CR channel
to within 3 bits/s/Hz for all channel parameters. In particular, we present
several new outer bounds which we achieve to within a constant gap by proper
selection of Gaussian input distributions in a simple rate-splitting and
superposition coding-based inner bound. The inner and outer bounds are
numerically evaluated to show that the actual gap can be far less than 3
bits/s/Hz.
|
1102.3226
|
A New Capacity Result for the Z-Gaussian Cognitive Interference Channel
|
cs.IT math.IT
|
This work proposes a novel outer bound for the Gaussian cognitive
interference channel in strong interference at the primary receiver based on
the capacity of a multi-antenna broadcast channel with degraded message set. It
then shows that for the Z-channel, i.e., when the secondary receiver
experiences no interference and the primary receiver experiences strong
interference, the proposed outer bound not only is the tightest among known
bounds but is actually achievable for sufficiently strong interference. The
latter is a novel capacity result that from numerical evaluations appears to be
generalizable to a larger (i.e., non-Z) class of Gaussian channels.
|
1102.3227
|
The Capacity of the Interference Channel with a Cognitive Relay in Very
Strong Interference
|
cs.IT math.IT
|
The interference channel with a cognitive relay consists of a classical
interference channel with two sourcedestination pairs and with an additional
cognitive relay that has a priori knowledge of the sources' messages and aids
in the sources' transmission. We derive a new outer bound for this channel
using an argument originally devised for the "more capable" broadcast channel,
and show the achievability of the proposed outer bound in the "very strong
interference" regime, a class of channels where there is no loss in optimality
if both destinations decode both messages. This result is analogous to the
"very strong interference" capacity result for the classical interference
channel and for the cognitive interference channel, and is the first capacity
known capacity result for the general interference channel with a cognitive
relay.
|
1102.3235
|
K-user Interference Channels: General Outer Bound and Sum-capacity for
Certain Gaussian Channels
|
cs.IT math.IT
|
This paper derives an outer bound on the capacity region of a general
memoryless interference channel with an arbitrary number of users. The
derivation follows from a generalization of the techniques developed by Kramer
and by Etkin et al for the Gaussian two-user channel. The derived bound is the
first known outer bound valid for any memoryless channel. In Gaussian noise,
classes of channels for which the proposed bound gives the sum-rate capacity
are identified, including degraded channels and a class of Z-channels.
|
1102.3241
|
Some limits to nonparametric estimation for ergodic processes
|
cs.IT math.IT
|
A new negative result for nonparametric distribution estimation of binary
ergodic processes is shown. The problem of estimation of distribution with any
degree of accuracy is studied. Then it is shown that for any countable class of
estimators there is a zero-entropy binary ergodic process that is inconsistent
with the class of estimators. Our result is different from other negative
results for universal forecasting scheme of ergodic processes. We also
introduce a related result by B. Weiss.
|
1102.3242
|
Weak randomness and Kamae's theorem on normal numbers
|
cs.IT math.IT
|
A function from sequences to their subsequences is called selection function.
A selection function is called admissible (with respect to normal numbers) if
for all normal numbers, their subsequences obtained by the selection function
are normal numbers.
In Kamae (1973) selection functions that are not depend on sequences (depend
only on coordinates) are studied, and their necessary and sufficient condition
for admissibility is given. In this paper we introduce a notion of weak
randomness and study an algorithmic analogy to the Kamae's theorem.
|
1102.3243
|
On the Capacity of Abelian Group Codes Over Discrete Memoryless Channels
|
cs.IT math.IT
|
For most discrete memoryless channels, there does not exist a linear code for
the channel which uses all of the channel's input symbols. Therefore, linearity
of the code for such channels is a very restrictive condition and there should
be a loosening of the algebraic structure of the code to a degree that the code
can admit any channel input alphabet. For any channel input alphabet size,
there always exists an Abelian group structure defined on the alphabet. We
investigate the capacity of Abelian group codes over discrete memoryless
channels and provide lower and upper bounds on the capacity.
|
1102.3260
|
Adaptive Cluster Expansion for Inferring Boltzmann Machines with Noisy
Data
|
physics.data-an cond-mat.stat-mech cs.LG q-bio.NC q-bio.QM
|
We introduce a procedure to infer the interactions among a set of binary
variables, based on their sampled frequencies and pairwise correlations. The
algorithm builds the clusters of variables contributing most to the entropy of
the inferred Ising model, and rejects the small contributions due to the
sampling noise. Our procedure successfully recovers benchmark Ising models even
at criticality and in the low temperature phase, and is applied to
neurobiological data.
|
1102.3268
|
Exact observability, square functions and spectral theory
|
math.FA cs.SY math.OC
|
In the first part of this article we introduce the notion of a
backward-forward conditioning (BFC) system that generalises the notion of
zero-class admissibiliy introduced in [Xu,Liu,Yung]. We can show that unless
the spectum contains a halfplane, the BFC property occurs only in siutations
where the underlying semigroup extends to a group. In a second part we present
a sufficient condition for exact observability in Banach spaces that is
designed for infinite-dimensional output spaces and general strongly continuous
semigroups. To obtain this we make use of certain weighted square function
estimates. Specialising to the Hilbert space situation we obtain a result for
contraction semigroups without an analyticity condition on the semigroup.
|
1102.3288
|
Compressive MUSIC with optimized partial support for joint sparse
recovery
|
cs.IT math.IT
|
Multiple measurement vector (MMV) problem addresses the identification of
unknown input vectors that share common sparse support. The MMV problems had
been traditionally addressed either by sensor array signal processing or
compressive sensing. However, recent breakthrough in this area such as
compressive MUSIC (CS-MUSIC) or subspace-augumented MUSIC (SA-MUSIC) optimally
combines the compressive sensing (CS) and array signal processing such that
$k-r$ supports are first found by CS and the remaining $r$ supports are
determined by generalized MUSIC criterion, where $k$ and $r$ denote the
sparsity and the independent snapshots, respectively. Even though such hybrid
approach significantly outperforms the conventional algorithms, its performance
heavily depends on the correct identification of $k-r$ partial support by
compressive sensing step, which often deteriorate the overall performance. The
main contribution of this paper is, therefore, to show that as long as $k-r+1$
correct supports are included in any $k$-sparse CS solution, the optimal $k-r$
partial support can be found using a subspace fitting criterion, significantly
improving the overall performance of CS-MUSIC. Furthermore, unlike the single
measurement CS counterpart that requires infinite SNR for a perfect support
recovery, we can derive an information theoretic sufficient condition for the
perfect recovery using CS-MUSIC under a {\em finite} SNR scenario.
|
1102.3289
|
Belief propagation for joint sparse recovery
|
cs.IT math.IT
|
Compressed sensing (CS) demonstrates that sparse signals can be recovered
from underdetermined linear measurements. We focus on the joint sparse recovery
problem where multiple signals share the same common sparse support sets, and
they are measured through the same sensing matrix. Leveraging a recent
information theoretic characterization of single signal CS, we formulate the
optimal minimum mean square error (MMSE) estimation problem, and derive a
belief propagation algorithm, its relaxed version, for the joint sparse
recovery problem and an approximate message passing algorithm. In addition,
using density evolution, we provide a sufficient condition for exact recovery.
|
1102.3294
|
Causal Rate Distortion Function on Abstract Alphabets and Optimal
Reconstruction Kernel
|
cs.IT math.IT
|
A Causal rate distortion function with a general fidelity criterion is
formulated on abstract alphabets and the optimal reconstruction kernel is
derived, which consists of a product of causal kernels. In the process, general
abstract spaces are introduced to show existence of the minimizing kernel using
weak*-convergence. Certain properties of the causal rate distortion function
are presented.
|
1102.3295
|
General Linear Quadratic Optimal Stochastic Control Problem Driven by a
Brownian Motion and a Poisson Random Martingale Measure with Random
Coefficients
|
math.OC cs.SY
|
The main purpose of this paper is to discuss detailed the stochastic LQ
control problem with random coefficients where the linear system is a
multidimensional stochastic differential equation driven by a multidimensional
Brownian motion and a Poisson random martingale measure. In the paper, we will
establish the connections of the multidimensional Backward stochastic Riccati
equation with jumps (BSRDEJ in short form) to the stochastic LQ problem and to
the associated Hamilton systems. By the connections, we show the optimal
control have the state feedback representation. Moreover, we will show the
existence and uniqueness result of the multidimensional BSRDEJ for the case
where the generator is bounded linear dependence with respect to the unknowns
martingale term.
|
1102.3298
|
A family of fast-decodable MIDO codes from crossed-product algebras over
Q
|
cs.IT math.IT math.RA
|
Multiple Input Double Output (MIDO) asymmetric space-time codes for 4
transmit antennas and 2 receive antennas can be employed in the downlink from
base stations to portable devices. Previous MIDO code constructions with low
Maximum Likelihood (ML) decoding complexity, full diversity and the
non-vanishing determinant (NVD) property are mostly based on cyclic division
algebras. In this paper, a new family of MIDO codes with the NVD property based
on crossed-product algebras over Q is introduced. Fast decodability follows
naturally from the structure of the codewords which consist of four generalized
Alamouti blocks. The associated ML complexity order is the lowest known for
full-rate MIDO codes (O(M^{10}) instead of O(M^{16}) with respect to the real
constellation size M). Numerical simulations show that these codes have a
performance from comparable up to 1dB gain compared to the best known MIDO code
with the same complexity.
|
1102.3306
|
Efficient Error-Correcting Geocoding
|
cs.IR cs.DS
|
We study the problem of resolving a perhaps misspelled address of a location
into geographic coordinates of latitude and longitude. Our data structure
solves this problem within a few milliseconds even for misspelled and
fragmentary queries. Compared to major geographic search engines such as Google
or Bing we achieve results of significantly better quality.
|
1102.3328
|
An Efficient and Integrated Algorithm for Video Enhancement in
Challenging Lighting Conditions
|
cs.GR cs.CV
|
We describe a novel integrated algorithm for real-time enhancement of video
acquired under challenging lighting conditions. Such conditions include low
lighting, haze, and high dynamic range situations. The algorithm automatically
detects the dominate source of impairment, then depending on whether it is low
lighting, haze or others, a corresponding pre-processing is applied to the
input video, followed by the core enhancement algorithm. Temporal and spatial
redundancies in the video input are utilized to facilitate real-time processing
and to improve temporal and spatial consistency of the output. The proposed
algorithm can be used as an independent module, or be integrated in either a
video encoder or a video decoder for further optimizations.
|
1102.3340
|
Multi-skill Collaborative Teams based on Densest Subgraphs
|
cs.SI cs.DS physics.soc-ph
|
We consider the problem of identifying a team of skilled individuals for
collaboration, in the presence of a social network. Each node in the social
network may be an expert in one or more skills. Edge weights specify affinity
or collaborative compatibility between respective nodes. Given a project that
requires a set of specified number of skilled individuals in each area of
expertise, the goal is to identify a team that maximizes the collaborative
compatibility. For example, the requirement may be to form a team that has at
least three databases experts and at least two theory experts. We explore team
formation where the collaborative compatibility objective is measured as the
density of the induced subgraph on selected nodes. The problem of maximizing
density is NP-hard even when the team requires individuals of only one skill.
We present a 3-approximation algorithm that improves upon a naive extension of
the previously known algorithm for densest at least $k$ subgraph problem. We
further show how the same approximation can be extended to a special case of
multiple skills. Our problem generalizes the formulation studied by Lappas et
al. [KDD '09] who measure team compatibility in terms of diameter or spanning
tree costs. Experiments are performed on a crawl of the DBLP graph where
individuals can be skilled in at most four areas - theory, databases, data
mining, and artificial intelligence. In addition to our main algorithm, we also
present heuristic extensions to trade off between the size of the solution and
its induced density. These density-based algorithms outperform the
diameter-based objective on several metrics for assessing the collaborative
compatibility of teams. The solutions suggested are also intuitively meaningful
and scale well with the increase in the number of skilled individuals required.
|
1102.3341
|
Reasoning about Social Choice Functions
|
cs.MA
|
We introduce a logic specifically designed to support reasoning about social
choice functions. The logic includes operators to capture strategic ability,
and operators to capture agent preferences. We establish a correspondence
between formulae in the logic and properties of social choice functions, and
show that the logic is expressively complete with respect to social choice
functions, i.e., that every social choice function can be characterised as a
formula of the logic. We prove that the logic is decidable, and give a complete
axiomatization. To demonstrate the value of the logic, we show in particular
how it can be applied to the problem of determining whether a social choice
function is strategy-proof.
|
1102.3350
|
On conjugacy classes of subgroups of the general linear group and cyclic
orbit codes
|
cs.IT math.IT
|
Orbit codes are a family of codes employable for communications on a random
linear network coding channel. The paper focuses on the classification of these
codes. We start by classifying the conjugacy classes of cyclic subgroups of the
general linear group. As a result, we are able to focus the study of cyclic
orbit codes to a restricted family of them.
|
1102.3390
|
Trellis-Based Check Node Processing for Low-Complexity Nonbinary LP
Decoding
|
cs.IT math.IT
|
Linear Programming (LP) decoding is emerging as an attractive alternative to
decode Low-Density Parity-Check (LDPC) codes. However, the earliest LP decoders
proposed for binary and nonbinary LDPC codes are not suitable for use at
moderate and large code lengths. To overcome this problem, Vontobel et al.
developed an iterative Low-Complexity LP (LCLP) decoding algorithm for binary
LDPC codes. The variable and check node calculations of binary LCLP decoding
algorithm are related to those of binary Belief Propagation (BP). The present
authors generalized this work to derive an iterative LCLP decoding algorithm
for nonbinary linear codes. Contrary to binary LCLP, the variable and check
node calculations of this algorithm are in general different from that of
nonbinary BP. The overall complexity of nonbinary LCLP decoding is linear in
block length; however the complexity of its check node calculations is
exponential in the check node degree. In this paper, we propose a modified BCJR
algorithm for efficient check node processing in the nonbinary LCLP decoding
algorithm. The proposed algorithm has complexity linear in the check node
degree. We also introduce an alternative state metric to improve the run time
of the proposed algorithm. Simulation results are presented for $(504, 252)$
and $(1008, 504)$ nonbinary LDPC codes over $\mathbb{Z}_4$.
|
1102.3392
|
Space-Time Coding over Fading Channels with Stable Noise
|
cs.IT math.IT
|
This paper addresses the performance of space-time coding over fading
channels with impulsive noise which is known to accurately capture network
interference. We use the symmetric alpha stable noise distribution and adopt
two models which assume dependent and independent noise components across
receive antennas. We derive pairwise error probability (PEP) of orthogonal
space-time block codes (STBC) with a benchmark genie-aided receiver (GAR), or
the minimum distance receiver (MDR) which is optimal in the Gaussian case. For
general space-time codes we propose a maximum-likelihood (ML) receiver, and its
approximation at high signal-to-noise ratio (SNR). The resulting asymptotically
optimal receiver (AOR) does not depend on noise parameters and is
computationally simple. Monte-Carlo simulations are used to supplement our
analytical results and compare the performance of the receivers.
|
1102.3396
|
Detecting Separation in Robotic and Sensor Networks
|
cs.RO cs.SY
|
In this paper we consider the problem of monitoring detecting separation of
agents from a base station in robotic and sensor networks. Such separation can
be caused by mobility and/or failure of the agents. While separation/cut
detection may be performed by passing messages between a node and the base in
static networks, such a solution is impractical for networks with high
mobility, since routes are constantly changing. We propose a distributed
algorithm to detect separation from the base station. The algorithm consists of
an averaging scheme in which every node updates a scalar state by communicating
with its current neighbors. We prove that if a node is permanently disconnected
from the base station, its state converges to $0$. If a node is connected to
the base station in an average sense, even if not connected in any instant,
then we show that the expected value of its state converges to a positive
number. Therefore, a node can detect if it has been separated from the base
station by monitoring its state. The effectiveness of the proposed algorithm is
demonstrated through simulations, a real system implementation and experiments
involving both static as well as mobile networks.
|
1102.3410
|
Capacity Bounds for Multiuser Channels with Non-Causal Channel State
Information at the Transmitters
|
cs.IT math.IT
|
In this paper, capacity inner and outer bounds are established for the
multiuser channels with Channel State Information (CSI) known non-causally at
the transmitters: The Multiple Access Channel (MAC), the Broadcast Channel (BC)
with common information, and the Relay Channel (RC). For each channel, the
actual capacity region is also derived in some special cases. Specifically, it
is shown that for some deterministic models with non-causal CSI at the
transmitters, similar to Costa's Gaussian channel, the availability of CSI at
the deterministic receivers does not affect the capacity region.
|
1102.3413
|
The Capacity Region of p-Transmitter/q-Receiver Multiple-Access Channels
with Common Information
|
cs.IT math.IT
|
This paper investigates the capacity problem for some multiple-access
scenarios with cooperative transmitters. First, a general Multiple-Access
Channel (MAC) with common information, i.e., a scenario where p transmitters
send private messages and also a common message to q receivers and each
receiver decodes all of the messages, is considered. The capacity region of the
discrete memoryless channel is characterized. Then, the general Gaussian fading
MAC with common information wherein partial Channel State Information (CSI) is
available at the transmitters (CSIT) and perfect CSI is available at the
receivers (CSIR) is investigated. A coding theorem is proved for this model
that yields an exact characterization of the throughput capacity region.
Finally, a two-transmitter/one-receiver Gaussian fading MAC with conferencing
encoders with partial CSIT and perfect CSIR is studied and its capacity region
is determined. For the Gaussian fading models with CSIR only (transmitters have
no access to CSIT), some numerical examples and simulation results are provided
for Rayleigh fading.
|
1102.3493
|
Scalable constructions of fractional repetition codes in distributed
storage systems
|
cs.IT cs.DC math.IT
|
In distributed storage systems built using commodity hardware, it is
necessary to have data redundancy in order to ensure system reliability. In
such systems, it is also often desirable to be able to quickly repair storage
nodes that fail. We consider a scheme--introduced by El Rouayheb and
Ramchandran--which uses combinatorial block design in order to design storage
systems that enable efficient (and exact) node repair. In this work, we
investigate systems where node sizes may be much larger than replication
degrees, and explicitly provide algorithms for constructing these storage
designs. Our designs, which are related to projective geometries, are based on
the construction of bipartite cage graphs (with girth 6) and the concept of
mutually-orthogonal Latin squares. Via these constructions, we can guarantee
that the resulting designs require the fewest number of storage nodes for the
given parameters, and can further show that these systems can be easily
expanded without need for frequent reconfiguration.
|
1102.3495
|
Diversity and Multiplexing Tradeoff in the Uplink of Cellular Systems
with Linear MMSE Receiver
|
cs.IT math.IT
|
In this paper, we extend the diversity and multiplexing tradeoff (DMT)
analysis from point-to-point channels to cellular systems to evaluate the
impact of inter-cell interference on the system reliability and efficiency.
Fundamental tradeoff among diversity order, multiplexing gain and inter-cell
interference intensity is characterized to reveal the capability of multiple
antennas in cellular systems. And the detrimental effects of the inter-cell
interference on the system performance of diversity and multiplexing is
presented and analyzed.
|
1102.3500
|
Improved Rate-Equivocation Regions for Secure Cooperative Communication
|
cs.IT math.IT
|
A simple four node network in which cooperation improves the
information-theoretic secrecy is studied. The channel consists of two senders,
a receiver, and an eavesdropper. One or both senders transmit confidential
messages to the receiver, while the eavesdropper tries to decode the
transmitted message. The main result is the derivation of a newly achievable
rate-equivocation region that is shown to be larger than a rate-equivocation
region derived by Lai and El Gamal for the relay-eavesdropper channel. When the
rate of the helping interferer is zero, the new rate-equivocation region
reduces to the capacity-equivocation region over the wire-tap channel, hence,
the new achievability scheme can be seen as a generalization of a coding scheme
proposed by Csiszar and Korner. This result can naturally be combined with a
rate-equivocation region given by Tang et al. (for the interference assisted
secret communication), yielding an even larger achievable rate-equivocation
region.
|
1102.3508
|
Online Learning of Rested and Restless Bandits
|
math.OC cs.LG
|
In this paper we study the online learning problem involving rested and
restless multiarmed bandits with multiple plays. The system consists of a
single player/user and a set of K finite-state discrete-time Markov chains
(arms) with unknown state spaces and statistics. At each time step the player
can play M arms. The objective of the user is to decide for each step which M
of the K arms to play over a sequence of trials so as to maximize its long term
reward. The restless multiarmed bandit is particularly relevant to the
application of opportunistic spectrum access (OSA), where a (secondary) user
has access to a set of K channels, each of time-varying condition as a result
of random fading and/or certain primary users' activities.
|
1102.3513
|
Layered Index-less Indexed Flash Codes for Improving Average Performance
|
cs.IT math.IT
|
In the present paper, a modification of the Index-less Indexed Flash Codes
(ILIFC) for flash memory storage system is presented. Although the ILIFC
proposed by Mahdavifar et al. has excellent worst case performance, the ILIFC
can be further improved in terms of the average case performance. The proposed
scheme, referred to as the {\em layered ILIFC}, is based on the ILIFC. However,
the primary focus of the present study is the average case performance. The
main feature of the proposed scheme is the use of the layer-based index coding
to represent indices of information bits. The layer index coding promotes the
uniform use of cell levels, which leads to better average case performance.
Based on experiments, the proposed scheme achieves a larger average number of
rewritings than the original ILIFC without loss of worst case performance.
|
1102.3520
|
On Multiple Hypothesis Testing with Rejection Option
|
cs.IT math.IT
|
We study the problem of multiple hypothesis testing (HT) in view of a
rejection option. That model of HT has many different applications. Errors in
testing of M hypotheses regarding the source distribution with an option of
rejecting all those hypotheses are considered. The source is discrete and
arbitrarily varying (AVS). The tradeoffs among error probability
exponents/reliabilities associated with false acceptance of rejection decision
and false rejection of true distribution are investigated and the optimal
decision strategies are outlined. The main result is specialized for discrete
memoryless sources (DMS) and studied further. An interesting insight that the
analysis implies is the phenomenon (comprehensible in terms of
supervised/unsupervised learning) that in optimal discrimination within M
hypothetical distributions one permits always lower error than in deciding to
decline the set of hypotheses. Geometric interpretations of the optimal
decision schemes are given for the current and known bounds in multi-HT for
AVS's.
|
1102.3526
|
Linear Error Correcting Codes with Anytime Reliability
|
cs.IT cs.SY math.IT math.OC
|
We consider rate R = k/n causal linear codes that map a sequence of
k-dimensional binary vectors {b_t} to a sequence of n-dimensional binary
vectors {c_t}, such that each c_t is a function of {b_1,b_2,...,b_t}. Such a
code is called anytime reliable, for a particular binary-input memoryless
channel, if at each time, probability of making an error about a source bit
that was sent d time instants ago decays exponentially in d. Anytime reliable
codes are useful in interactive communication problems and, in particular, can
be used to stabilize unstable plants across noisy channels. Schulman proved the
existence of such codes which, due to their structure, he called tree codes;
however, to date, no explicit constructions and tractable decoding algorithms
have been devised. In this paper, we show the existence of anytime reliable
"linear" codes with "high probability", i.e., suitably chosen random linear
causal codes are anytime reliable with high probability. The key is to consider
time-invariant codes (i.e., ones with Toeplitz generator and parity check
matrices) which obviates the need to union bound over all times. For the binary
erasure channel we give a simple ML decoding algorithm whose average complexity
is constant per time iteration and for which the probability that complexity at
a given time t exceeds KC^3 decays exponentially in C. We show the efficacy of
the method by simulating the stabilization of an unstable plant across a BEC,
and remark on the tradeoffs between the utilization of the communication
resources and the control performance.
|
1102.3527
|
Generation of Innovative and Sparse Encoding Vectors for Broadcast
Systems with Feedback
|
cs.IT cs.CC math.IT
|
In the application of linear network coding to wireless broadcasting with
feedback, we prove that the problem of determining the existence of an
innovative encoding vector is NP-complete when the finite field size is two.
When the finite field size is larger than or equal to the number of users, it
is shown that we can always find an encoding vector which is both innovative
and sparse. The sparsity can be utilized in speeding up the decoding process.
An efficient algorithm to generate innovative and sparse encoding vectors is
developed. Simulations show that the delay performance of our scheme with
binary finite field outperforms a number of existing schemes in terms of
average and worst-case delay.
|
1102.3569
|
Optimality of Network Coding in Packet Networks
|
cs.IT cs.DS math.IT
|
We resolve the question of optimality for a well-studied packetized
implementation of random linear network coding, called PNC. In PNC, in contrast
to the classical memoryless setting, nodes store received information in memory
to later produce coded packets that reflect this information. PNC is known to
achieve order optimal stopping times for the many-to-all multicast problem in
many settings.
We give a reduction that captures exactly how PNC and other network coding
protocols use the memory of the nodes. More precisely, we show that any such
protocol implementation induces a transformation which maps an execution of the
protocol to an instance of the classical memoryless setting. This allows us to
prove that, for any (non-adaptive dynamic) network, PNC converges with high
probability in optimal time. In other words, it stops at exactly the first time
in which in hindsight it was possible to route information from the sources to
each receiver individually.
Our technique also applies to variants of PNC, in which each node uses only a
finite buffer. We show that, even in this setting, PNC stops exactly within the
time in which in hindsight it was possible to route packets given the memory
constraint, i.e., that the memory used at each node never exceeds its buffer
size. This shows that PNC, even without any feedback or explicit memory
management, allows to keep minimal buffer sizes while maintaining its capacity
achieving performance.
|
1102.3578
|
Onset of Synchronization in Weighted Complex Networks: the Effect of
Weight-Degree Correlation
|
nlin.CD cs.SI physics.soc-ph
|
By numerical simulations, we investigate the onset of synchronization of
networked phase oscillators under two different weighting schemes. In scheme-I,
the link weights are correlated to the product of the degrees of the connected
nodes, so this kind of networks is named as the weight-degree correlated (WDC)
network. In scheme-II, the link weights are randomly assigned to each link
regardless of the node degrees, so this kind of networks is named as the
weight-degree uncorrelated (WDU) network. Interestingly, it is found that by
increasing a parameter that governs the weight distribution, the onset of
synchronization in WDC network is monotonically enhanced, while in WDU network
there is a reverse in the synchronization performance. We investigate this
phenomenon from the viewpoint of gradient network, and explain the contrary
roles of coupling gradient on network synchronization: gradient promotes
synchronization in WDC network, while deteriorates synchronization in WDU
network. The findings highlight the fact that, besides the link weight, the
correlation between the weight and node degree is also important to the network
dynamics.
|
1102.3579
|
Cooperative Interference Control for Spectrum Sharing in OFDMA Cellular
Systems
|
cs.IT math.IT
|
This paper studies cooperative schemes for the inter-cell interference
control in orthogonal-frequency-divisionmultiple- access (OFDMA) cellular
systems. The downlink transmission in a simplified two-cell system is examined,
where both cells simultaneously access the same frequency band using OFDMA. The
joint power and subcarrier allocation over the two cells is investigated for
maximizing their sum throughput with both centralized and decentralized
implementations. Particularly, the decentralized allocation is achieved via a
new cooperative interference control approach, whereby the two cells
independently implement resource allocation to maximize individual throughput
in an iterative manner, subject to a set of mutual interference power
constraints. Simulation results show that the proposed decentralized resource
allocation schemes achieve the system throughput close to that by the
centralized scheme, and provide substantial throughput gains over existing
schemes.
|
1102.3584
|
Urban road networks -- Spatial networks with universal geometric
features? A case study on Germany's largest cities
|
physics.data-an cs.SI physics.soc-ph
|
Urban road networks have distinct geometric properties that are partially
determined by their (quasi-) two-dimensional structure. In this work, we study
these properties for 20 of the largest German cities. We find that the
small-scale geometry of all examined road networks is extremely similar. The
object-size distributions of road segments and the resulting cellular
structures are characterised by heavy tails. As a specific feature, a large
degree of rectangularity is observed in all networks, with link angle
distributions approximately described by stretched exponential functions. We
present a rigorous statistical analysis of the main geometric characteristics
and discuss their mutual interrelationships. Our results demonstrate the
fundamental importance of cost-efficiency constraints for in time evolution of
urban road networks.
|
1102.3603
|
A Graph Theoretical Approach for Network Coding in Wireless Body Area
Networks
|
cs.IT math.IT
|
Modern medical wireless systems, such as wireless body area networks (WBANs),
are applications of wireless networks that can be used as a tool of data
transmission between patients and doctors. Accuracy of data transmission is an
important requirement for such systems. In this paper, we will propose a WBAN
which is robust against erasures and describe its properties using graph
theoretic techniques.
|
1102.3604
|
Algebraic Decoding of Negacyclic Codes Over Z_4
|
math.CO cs.IT math.IT
|
In this article we investigate Berlekamp's negacyclic codes and discover that
these codes, when considered over the integers modulo 4, do not suffer any of
the restrictions on the minimum distance observed in Berlekamp's original
papers. The codes considered here have minimim Lee distance at least 2t+1,
where the generator polynomial of the code has roots z,z^3,...,z^{2t+1} for a
primitive 2nth root of unity z in a Galois extension of Z4. No restriction on t
is imposed. We present an algebraic decoding algorithm for this class of codes
that corrects any error pattern of Lee weight at most t. Our treatment uses
Grobner bases and the decoding complexity is quadratic in t.
|
1102.3605
|
Nonbinary Quantum Codes from Two-Point Divisors on Hermitian Curves
|
cs.IT math.IT
|
Sarvepalli and Klappenecker showed how classical one-point codes on the
Hermitian curve can be used to construct quantum codes. Homma and Kim
determined the parameters of a larger family of codes, the two-point codes. In
quantum error-correction, the observed presence of asymmetry in some quantum
channels led to the study of asymmetric quantum codes (AQECCs) where we no
longer assume that the different types of errors are equiprobable. This paper
considers quantum codes constructed from the two-point codes. In the asymmetric
case, we show strict improvements over all possible finite fields for a range
of designed distances. We produce large dimension pure AQECC and small
dimension impure AQECC that have better parameters than AQECC from one-point
codes. Numerical results for the Hermitian curves over F16 and F64 are used to
illustrate the gain.
|
1102.3617
|
Wireless Secrecy in Large-Scale Networks
|
cs.IT cs.NI math.IT
|
The ability to exchange secret information is critical to many commercial,
governmental, and military networks. The intrinsically secure communications
graph (iS-graph) is a random graph which describes the connections that can be
securely established over a large-scale network, by exploiting the physical
properties of the wireless medium. This paper provides an overview of the main
properties of this new class of random graphs. We first analyze the local
properties of the iS-graph, namely the degree distributions and their
dependence on fading, target secrecy rate, and eavesdropper collusion. To
mitigate the effect of the eavesdroppers, we propose two techniques that
improve secure connectivity. Then, we analyze the global properties of the
iS-graph, namely percolation on the infinite plane, and full connectivity on a
finite region. These results help clarify how the presence of eavesdroppers can
compromise secure communication in a large-scale network.
|
1102.3669
|
Efficient File Synchronization: a Distributed Source Coding Approach
|
cs.IT math.IT
|
The problem of reconstructing a source sequence with the presence of decoder
side-information that is mis-synchronized to the source due to deletions is
studied in a distributed source coding framework. Motivated by practical
applications, the deletion process is assumed to be bursty and is modeled by a
Markov chain. The minimum rate needed to reconstruct the source sequence with
high probability is characterized in terms of an information theoretic
expression, which is interpreted as the amount of information of the deleted
content and the locations of deletions, subtracting "nature's secret", that is,
the uncertainty of the locations given the source and side-information. For
small bursty deletion probability, the asymptotic expansion of the minimum rate
is computed.
|
1102.3680
|
Foundations for Understanding and Building Conscious Systems using
Stable Parallel Looped Dynamics
|
cs.AI q-bio.NC
|
The problem of consciousness faced several challenges for a few reasons: (a)
a lack of necessary and sufficient conditions, without which we would not know
how close we are to the solution, (b) a lack of a synthesis framework to build
conscious systems and (c) a lack of mechanisms explaining the transition
between the lower-level chemical dynamics and the higher-level abstractions. In
this paper, I address these issues using a new framework. The central result is
that a person is 'minimally' conscious if and only if he knows at least one
truth. This lets us move away from the vagueness surrounding consciousness and
instead focus equivalently on: (i) what truths are and how our brain
represents/relates them to each other and (ii) how we attain a feeling of
knowing for a truth. For the former problem, since truths are things that do
not change, I replace the abstract notion with a dynamical one called fixed
sets. These sets are guaranteed to exist for our brain and other stable
parallel looped systems. The relationships between everyday events are now
built using relationships between fixed sets, until our brain creates a unique
dynamical state called the self-sustaining threshold 'membrane' of fixed sets.
For the latter problem, I present necessary and sufficient conditions for
attaining a feeling of knowing using a definition of continuity applied to
abstractions. Combining these results, I now say that a person is minimally
conscious if and only if his brain has a self-sustaining dynamical membrane
with abstract continuous paths. A synthetic system built to satisfy this
equivalent self-sustaining membrane condition appears indistinguishable from
human consciousness.
|
1102.3713
|
Optimal Control of Inhomogeneous Ensembles
|
math.OC cs.SY quant-ph
|
Inhomogeneity, in its many forms, appears frequently in practical physical
systems. Readily apparent in quantum systems, inhomogeneity is caused by
hardware imperfections, measurement inaccuracies, and environmental variations,
and subsequently limits the performance and efficiency achievable in current
experiments. In this paper, we provide a systematic methodology to
mathematically characterize and optimally manipulate inhomogeneous ensembles
with concepts taken from ensemble control. In particular, we develop a
computational method to solve practical quantum pulse design problems cast as
optimal ensemble control problems, based on multidimensional pseudospectral
approximations. We motivate the utility of this method by designing pulses for
both standard and novel applications. We also show the convergence of the
pseudospectral method for optimal ensemble control. The concepts developed here
are applicable beyond quantum control, such as to neuron systems, and
furthermore to systems with by parameter uncertainty, which pervade all areas
of science and engineering.
|
1102.3751
|
Utility-Privacy Tradeoff in Databases: An Information-theoretic Approach
|
cs.IT math.IT
|
Ensuring the usefulness of electronic data sources while providing necessary
privacy guarantees is an important unsolved problem. This problem drives the
need for an analytical framework that can quantify the safety of personally
identifiable information (privacy) while still providing a quantifable benefit
(utility) to multiple legitimate information consumers. This paper presents an
information-theoretic framework that promises an analytical model guaranteeing
tight bounds of how much utility is possible for a given level of privacy and
vice-versa. Specific contributions include: i) stochastic data models for both
categorical and numerical data; ii) utility-privacy tradeoff regions and the
encoding (sanization) schemes achieving them for both classes and their
practical relevance; and iii) modeling of prior knowledge at the user and/or
data source and optimal encoding schemes for both cases.
|
1102.3755
|
Cooperative Wideband Spectrum Sensing for the Centralized Cognitive
Radio Network
|
cs.IT math.IT
|
Various primary user (PU) radios have been allocated into fixed frequency
bands in the whole spectrum. A cognitive radio network (CRN) should be able to
perform the wideband spectrum sensing (WSS) to detect temporarily unoccupied
frequency bands. We summarize four occupancy features for the frequency bands.
1. The occupancy is sparse; 2. The frequency band allocation information is
fixed and common; 3. There are three categories for the frequency band usages;
4. The occupied frequency bands are common in the CRN. For the first time, we
consider all features as the prior knowledge in the compressed sensing based
cooperative WSS (CWSS) algorithm design for a centralized CRN. We propose a
modified orthogonal matching pursuit (Mod-OMP) algorithm and a modified
simultaneous orthogonal matching pursuit (Mod-SOMP) algorithm for the CWSS. We
compare the CWSS performance of Mod-OMP/Mod-SOMP with the original OMP/SOMP and
show the performance improvements.
|
1102.3758
|
Optimal Spectrum Management in Multiuser Interference Channels
|
cs.IT math.IT
|
In this paper, we study the non-convex problem of continuous frequency
optimal spectrum management in multiuser frequency selective interference
channels. Firstly, a simple pairwise channel condition for FDMA schemes to
achieve all Pareto optimal points of the rate region is derived. It enables
fully distributed global optimal decision making on whether any two users
should use orthogonal channels. Next, we present in detail an analytical
solution to finding the global optimum of sum-rate maximization in two-user
symmetric flat channels. Generalizing this solution to frequency selective
channels, a convex optimization is established that solves the global optimum.
Finally, we show that our method generalizes to K-user (K>=2) weighted sum-rate
maximization in asymmetric frequency selective channels, and transform this
classic non-convex optimization in the primal domain to an equivalent convex
optimization. The complexity is shown to be separable in its dependence on the
channel parameters and the power constraints.
|
1102.3763
|
On the Capacity Region of the Cognitive Interference Channel with
Unidirectional Destination Cooperation
|
cs.IT math.IT
|
The cognitive interference channel with unidirectional destination
cooperation (CIFC-UDC) is a variant of the cognitive interference channel
(CIFC) where the cognitive (secondary) destination not only decodes the
information sent from its sending dual but also helps enhance the communication
of the primary user. This channel is an extension of the original CIFC to
achieve a win-win solution under the coexistence condition. The CIFC-UDC
comprises a broadcast channel (BC), a relay channel (RC), as well as a
partially cooperative relay broadcast channel (PCRBC), and can be degraded to
any one of them. In this paper, we propose a new achievable rate region for the
dis-crete memoryless CIFC-UDC which improves the previous re-sults and includes
the largest known rate regions of the BC, the RC, the PCRBC and the CIFC. A new
outer bound is presented and proved to be tight for two classes of the
CIFC-UDCs, result-ing in the characterization of the capacity region.
|
1102.3828
|
Searching in one billion vectors: re-rank with source coding
|
cs.IR cs.CV
|
Recent indexing techniques inspired by source coding have been shown
successful to index billions of high-dimensional vectors in memory. In this
paper, we propose an approach that re-ranks the neighbor hypotheses obtained by
these compressed-domain indexing methods. In contrast to the usual
post-verification scheme, which performs exact distance calculation on the
short-list of hypotheses, the estimated distances are refined based on short
quantization codes, to avoid reading the full vectors from disk. We have
released a new public dataset of one billion 128-dimensional vectors and
proposed an experimental setup to evaluate high dimensional indexing algorithms
on a realistic scale. Experiments show that our method accurately and
efficiently re-ranks the neighbor hypotheses using little memory compared to
the full vectors representation.
|
1102.3830
|
A linear framework for region-based image segmentation and inpainting
involving curvature penalization
|
cs.CV cs.AI math.OC
|
We present the first method to handle curvature regularity in region-based
image segmentation and inpainting that is independent of initialization.
To this end we start from a new formulation of length-based optimization
schemes, based on surface continuation constraints, and discuss the connections
to existing schemes. The formulation is based on a \emph{cell complex} and
considers basic regions and boundary elements. The corresponding optimization
problem is cast as an integer linear program.
We then show how the method can be extended to include curvature regularity,
again cast as an integer linear program. Here, we are considering pairs of
boundary elements to reflect curvature. Moreover, a constraint set is derived
to ensure that the boundary variables indeed reflect the boundary of the
regions described by the region variables.
We show that by solving the linear programming relaxation one gets quite
close to the global optimum, and that curvature regularity is indeed much
better suited in the presence of long and thin objects compared to standard
length regularity.
|
1102.3833
|
Aligned Interference Neutralization and the Degrees of Freedom of the 2
User Interference Channel with Instantaneous Relay
|
cs.IT math.IT
|
It is well known that the classical 2 user Gaussian interference channel has
only 1 degree of freedom (DoF), which can be achieved by orthogonal time
division among the 2 users. It is also known that the use of conventional
relays, which introduce a processing delay of at least one symbol duration
relative to the direct paths between sources and destinations, does not
increase the DoF of the 2 user interference channel. The use of instantaneous
relays (relays-without-delay) has been explored for the single user
point-to-point setting and it is known that such a relay, even with memoryless
forwarding at the relay, can achieve a higher capacity than conventional
relays. In this work, we show that the 2 user interference channel with an
instantaneous relay, achieves 3/2 DoF. Thus, an instantaneous relay increases
not only the capacity but also the DoF of the 2 user interference channel. The
achievable scheme is inspired by the aligned interference neutralization scheme
recently proposed for the 2X2X2 interference channel. Remarkably the DoF gain
is achieved with memoryless relays, i.e., with relays that have no memory of
past received symbols.
|
1102.3852
|
On the Gain of Joint Processing of Pilot and Data Symbols in Stationary
Rayleigh Fading Channels
|
cs.IT math.IT
|
In many typical mobile communication receivers the channel is estimated based
on pilot symbols to allow for a coherent detection and decoding in a separate
processing step. Currently much work is spent on receivers which break up this
separation, e.g., by enhancing channel estimation based on reliability
information on the data symbols. In the present work, we evaluate the possible
gain of a joint processing of data and pilot symbols in comparison to the case
of a separate processing in the context of stationary Rayleigh flat-fading
channels. Therefore, we discuss the nature of the possible gain of a joint
processing of pilot and data symbols. We show that the additional information
that can be gained by a joint processing is captured in the temporal
correlation of the channel estimation error of the solely pilot based channel
estimation, which is not retrieved by the channel decoder in case of separate
processing. In addition, we derive a new lower bound on the achievable rate for
joint processing of pilot and data symbols.
|
1102.3865
|
Probability Based Clustering for Document and User Properties
|
cs.HC cs.IR
|
Information Retrieval systems can be improved by exploiting context
information such as user and document features. This article presents a model
based on overlapping probabilistic or fuzzy clusters for such features. The
model is applied within a fusion method which linearly combines several
retrieval systems. The fusion is based on weights for the different retrieval
systems which are learned by exploiting relevance feedback information. This
calculation can be improved by maintaining a model for each document and user
cluster. That way, the optimal retrieval system for each document or user type
can be identified and applied. The extension presented in this article allows
overlapping, probabilistic clusters of features to further refine the process.
|
1102.3866
|
Treatment of Semantic Heterogeneity in Information Retrieval
|
cs.IR
|
The first step to handle semantic heterogeneity should be the attempt to
enrich the semantic information about documents, i.e. to fill up the gaps in
the documents meta-data automatically. Section 2 describes a set of cascading
deductive and heuristic extraction rules, which were developed in the project
CARMEN for the domain of Social Sciences. The mapping between different
terminologies can be done by using intellectual, statistical and/or neural
network transfer modules. Intellectual transfers use cross-concordances between
different classification schemes or thesauri. Section 3 describes the creation,
storage and handling of such transfers.
|
1102.3867
|
Controllability properties for the one-dimensional Heat equation under
multiplicative or nonnegative additive controls with local mobile support
|
math.OC cs.SY
|
We discuss several new results on nonnegative approximate controllability for
the one-dimensional Heat equation governed by either multiplicative or
nonnegative additive control, acting within a proper subset of the space domain
at every moment of time. Our methods allow us to link these two types of
controls to some extend. The main results include approximate controllability
properties both for the static and mobile control supports.
|
1102.3868
|
Evolved preambles for MAX-SAT heuristics
|
cs.AI cs.NE
|
MAX-SAT heuristics normally operate from random initial truth assignments to
the variables. We consider the use of what we call preambles, which are
sequences of variables with corresponding single-variable assignment actions
intended to be used to determine a more suitable initial truth assignment for a
given problem instance and a given heuristic. For a number of well established
MAX-SAT heuristics and benchmark instances, we demonstrate that preambles can
be evolved by a genetic algorithm such that the heuristics are outperformed in
a significant fraction of the cases.
|
1102.3887
|
Active Clustering: Robust and Efficient Hierarchical Clustering using
Adaptively Selected Similarities
|
cs.IT cs.LG math.IT stat.ML
|
Hierarchical clustering based on pairwise similarities is a common tool used
in a broad range of scientific applications. However, in many problems it may
be expensive to obtain or compute similarities between the items to be
clustered. This paper investigates the hierarchical clustering of N items based
on a small subset of pairwise similarities, significantly less than the
complete set of N(N-1)/2 similarities. First, we show that if the intracluster
similarities exceed intercluster similarities, then it is possible to correctly
determine the hierarchical clustering from as few as 3N log N similarities. We
demonstrate this order of magnitude savings in the number of pairwise
similarities necessitates sequentially selecting which similarities to obtain
in an adaptive fashion, rather than picking them at random. We then propose an
active clustering method that is robust to a limited fraction of anomalous
similarities, and show how even in the presence of these noisy similarity
values we can resolve the hierarchical clustering using only O(N log^2 N)
pairwise similarities.
|
1102.3902
|
Polytope of Correct (Linear Programming) Decoding and Low-Weight
Pseudo-Codewords
|
cs.IT math.IT
|
We analyze Linear Programming (LP) decoding of graphical binary codes
operating over soft-output, symmetric and log-concave channels. We show that
the error-surface, separating domain of the correct decoding from domain of the
erroneous decoding, is a polytope. We formulate the problem of finding the
lowest-weight pseudo-codeword as a non-convex optimization (maximization of a
convex function) over a polytope, with the cost function defined by the channel
and the polytope defined by the structure of the code. This formulation
suggests new provably convergent heuristics for finding the lowest weight
pseudo-codewords improving in quality upon previously discussed. The algorithm
performance is tested on the example of the Tanner [155, 64, 20] code over the
Additive White Gaussian Noise (AWGN) channel.
|
1102.3919
|
Inferring Disease and Gene Set Associations with Rank Coherence in
Networks
|
q-bio.GN cs.AI cs.LG q-bio.MN
|
A computational challenge to validate the candidate disease genes identified
in a high-throughput genomic study is to elucidate the associations between the
set of candidate genes and disease phenotypes. The conventional gene set
enrichment analysis often fails to reveal associations between disease
phenotypes and the gene sets with a short list of poorly annotated genes,
because the existing annotations of disease causative genes are incomplete. We
propose a network-based computational approach called rcNet to discover the
associations between gene sets and disease phenotypes. Assuming coherent
associations between the genes ranked by their relevance to the query gene set,
and the disease phenotypes ranked by their relevance to the hidden target
disease phenotypes of the query gene set, we formulate a learning framework
maximizing the rank coherence with respect to the known disease phenotype-gene
associations. An efficient algorithm coupling ridge regression with label
propagation, and two variants are introduced to find the optimal solution of
the framework. We evaluated the rcNet algorithms and existing baseline methods
with both leave-one-out cross-validation and a task of predicting recently
discovered disease-gene associations in OMIM. The experiments demonstrated that
the rcNet algorithms achieved the best overall rankings compared to the
baselines. To further validate the reproducibility of the performance, we
applied the algorithms to identify the target diseases of novel candidate
disease genes obtained from recent studies of GWAS, DNA copy number variation
analysis, and gene expression profiling. The algorithms ranked the target
disease of the candidate genes at the top of the rank list in many cases across
all the three case studies. The rcNet algorithms are available as a webtool for
disease and gene set association analysis at
http://compbio.cs.umn.edu/dgsa_rcNet.
|
1102.3923
|
Concentration-Based Guarantees for Low-Rank Matrix Reconstruction
|
cs.LG stat.ML
|
We consider the problem of approximately reconstructing a partially-observed,
approximately low-rank matrix. This problem has received much attention lately,
mostly using the trace-norm as a surrogate to the rank. Here we study low-rank
matrix reconstruction using both the trace-norm, as well as the less-studied
max-norm, and present reconstruction guarantees based on existing analysis on
the Rademacher complexity of the unit balls of these norms. We show how these
are superior in several ways to recently published guarantees based on
specialized analysis.
|
1102.3931
|
Social consensus through the influence of committed minorities
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
We show how the prevailing majority opinion in a population can be rapidly
reversed by a small fraction p of randomly distributed committed agents who
consistently proselytize the opposing opinion and are immune to influence.
Specifically, we show that when the committed fraction grows beyond a critical
value p_c \approx 10%, there is a dramatic decrease in the time, T_c, taken for
the entire population to adopt the committed opinion. In particular, for
complete graphs we show that when p < p_c, T_c \sim \exp(\alpha(p)N), while for
p > p_c, T_c \sim \ln N. We conclude with simulation results for
Erd\H{o}s-R\'enyi random graphs and scale-free networks which show
qualitatively similar behavior.
|
1102.3936
|
AWGN Channel Analysis of Terminated LDPC Convolutional Codes
|
cs.IT math.IT
|
It has previously been shown that ensembles of terminated protograph-based
low-density parity-check (LDPC) convolutional codes have a typical minimum
distance that grows linearly with block length and that they are capable of
achieving capacity approaching iterative decoding thresholds on the binary
erasure channel (BEC). In this paper, we review a recent result that the
dramatic threshold improvement obtained by terminating LDPC convolutional codes
extends to the additive white Gaussian noise (AWGN) channel. Also, using a
(3,6)-regular protograph-based LDPC convolutional code ensemble as an example,
we perform an asymptotic trapping set analysis of terminated LDPC convolutional
code ensembles. In addition to capacity approaching iterative decoding
thresholds and linearly growing minimum distance, we find that the smallest
non-empty trapping set of a terminated ensemble grows linearly with block
length.
|
1102.3937
|
Axiomatic Ranking of Network Role Similarity
|
cs.SI physics.soc-ph
|
A key task in social network and other complex network analysis is role
analysis: describing and categorizing nodes according to how they interact with
other nodes. Two nodes have the same role if they interact with equivalent sets
of neighbors. The most fundamental role equivalence is automorphic equivalence.
Unfortunately, the fastest algorithms known for graph automorphism are
nonpolynomial. Moreover, since exact equivalence may be rare, a more meaningful
task is to measure the role similarity between any two nodes. This task is
closely related to the structural or link-based similarity problem that SimRank
attempts to solve. However, SimRank and most of its offshoots are not
sufficient because they do not fully recognize automorphically or structurally
equivalent nodes. In this paper we tackle two problems. First, what are the
necessary properties for a role similarity measure or metric? Second, how can
we derive a role similarity measure satisfying these properties? For the first
problem, we justify several axiomatic properties necessary for a role
similarity measure or metric: range, maximal similarity, automorphic
equivalence, transitive similarity, and the triangle inequality. For the second
problem, we present RoleSim, a new similarity metric with a simple iterative
computational method. We rigorously prove that RoleSim satisfies all the
axiomatic properties. We also introduce an iceberg RoleSim algorithm which can
guarantee to discover all pairs with RoleSim score no less than a user-defined
threshold $\theta$ without computing the RoleSim for every pair. We demonstrate
the superior interpretative power of RoleSim on both both synthetic and real
datasets.
|
1102.3939
|
A Sub-Space Method to Detect Multiple Wireless Microphone Signals in TV
Band White Space
|
cs.IT math.IT stat.AP
|
The main hurdle in the realization of dynamic spectrum access (DSA) systems
from physical layer perspective is the reliable sensing of low power licensed
users. One such scenario shows up in the unlicensed use of TV bands where the
TV Band Devices (TVBDs) are required to sense extremely low power wireless
microphones (WMs). The lack of technical standard among various wireless
manufacturers and the resemblance of certain WM signals to narrow-band
interference signals, such as spurious emissions, further aggravate the
problem. Due to these uncertainties, it is extremely difficult to abstract the
features of WM signals and hence develop robust sensing algorithms. To partly
counter these challenges, we develop a two-stage sub-space algorithm that
detects multiple narrow-band analog frequency-modulated signals generated by
WMs. The performance of the algorithm is verified by using experimentally
captured low power WM signals with received power ranging from -100 to -105
dBm. The problem of differentiating between the WM and other narrow-band
signals is left as a future work.
|
1102.3944
|
Fixed-length lossy compression in the finite blocklength regime
|
cs.IT math.IT
|
This paper studies the minimum achievable source coding rate as a function of
blocklength $n$ and probability $\epsilon$ that the distortion exceeds a given
level $d$. Tight general achievability and converse bounds are derived that
hold at arbitrary fixed blocklength. For stationary memoryless sources with
separable distortion, the minimum rate achievable is shown to be closely
approximated by $R(d) + \sqrt{\frac{V(d)}{n}} Q^{-1}(\epsilon)$, where $R(d)$
is the rate-distortion function, $V(d)$ is the rate dispersion, a
characteristic of the source which measures its stochastic variability, and
$Q^{-1}(\epsilon)$ is the inverse of the standard Gaussian complementary cdf.
|
1102.3947
|
Subspace Expanders and Matrix Rank Minimization
|
cs.IT math.IT
|
Matrix rank minimization (RM) problems recently gained extensive attention
due to numerous applications in machine learning, system identification and
graphical models. In RM problem, one aims to find the matrix with the lowest
rank that satisfies a set of linear constraints. The existing algorithms
include nuclear norm minimization (NNM) and singular value thresholding. Thus
far, most of the attention has been on i.i.d. Gaussian measurement operators.
In this work, we introduce a new class of measurement operators, and a novel
recovery algorithm, which is notably faster than NNM. The proposed operators
are based on what we refer to as subspace expanders, which are inspired by the
well known expander graphs based measurement matrices in compressed sensing. We
show that given an $n\times n$ PSD matrix of rank $r$, it can be uniquely
recovered from a minimal sampling of $O(nr)$ measurements using the proposed
structures, and the recovery algorithm can be cast as matrix inversion after a
few initial processing steps.
|
1102.3949
|
Sparse Signal Recovery with Temporally Correlated Source Vectors Using
Sparse Bayesian Learning
|
stat.ML cs.LG
|
We address the sparse signal recovery problem in the context of multiple
measurement vectors (MMV) when elements in each nonzero row of the solution
matrix are temporally correlated. Existing algorithms do not consider such
temporal correlations and thus their performance degrades significantly with
the correlations. In this work, we propose a block sparse Bayesian learning
framework which models the temporal correlations. In this framework we derive
two sparse Bayesian learning (SBL) algorithms, which have superior recovery
performance compared to existing algorithms, especially in the presence of high
temporal correlations. Furthermore, our algorithms are better at handling
highly underdetermined problems and require less row-sparsity on the solution
matrix. We also provide analysis of the global and local minima of their cost
function, and show that the SBL cost function has the very desirable property
that the global minimum is at the sparsest solution to the MMV problem.
Extensive experiments also provide some interesting results that motivate
future theoretical research on the MMV model.
|
1102.3989
|
Self-organization in social tagging systems
|
physics.soc-ph cs.SI
|
Individuals often imitate each other to fall into the typical group, leading
to a self-organized state of typical behaviors in a community. In this paper,
we model self-organization in social tagging systems and illustrate the
underlying interaction and dynamics. Specifically, we introduce a model in
which individuals adjust their own tagging tendency to imitate the average
tagging tendency. We found that when users are of low confidence, they tend to
imitate others and lead to a self-organized state with active tagging. On the
other hand, when users are of high confidence and are stubborn for changes,
tagging becomes inactive. We observe a phase transition at a critical level of
user confidence when the system changes from one regime to the other. The
distributions of post length obtained from the model are compared to real data
which show good agreements.
|
1102.4021
|
Privacy Preserving Spam Filtering
|
cs.LG cs.CR
|
Email is a private medium of communication, and the inherent privacy
constraints form a major obstacle in developing effective spam filtering
methods which require access to a large amount of email data belonging to
multiple users. To mitigate this problem, we envision a privacy preserving spam
filtering system, where the server is able to train and evaluate a logistic
regression based spam classifier on the combined email data of all users
without being able to observe any emails using primitives such as homomorphic
encryption and randomization. We analyze the protocols for correctness and
security, and perform experiments of a prototype system on a large scale spam
filtering task.
State of the art spam filters often use character n-grams as features which
result in large sparse data representation, which is not feasible to be used
directly with our training and evaluation protocols. We explore various data
independent dimensionality reduction which decrease the running time of the
protocol making it feasible to use in practice while achieving high accuracy.
|
1102.4085
|
On the Benefits of Partial Channel State Information for Repetition
Protocols in Block Fading Channels
|
cs.IT math.IT
|
This paper studies the throughput performance of HARQ (hybrid automatic
repeat request) protocols over block fading Gaussian channels. It proposes new
protocols that use the available feedback bit(s) not only to request a
retransmission, but also to inform the transmitter about the instantaneous
channel quality. An explicit protocol construction is given for any number of
retransmissions and any number of feedback bits. The novel protocol is shown to
simultaneously realize the gains of HARQ and of power control with partial CSI
(channel state information). Remarkable throughput improvements are shown,
especially at low and moderate SNR (signal to noise ratio), with respect to
protocols that use the feedback bits for retransmission request only. In
particular, for the case of a single retransmission and a single feedback bit,
it is shown that the repetition is not needed at low $\snr$ where the
throughput improvement is due to power control only. On the other hand, at high
SNR, the repetition is useful and the performance gain comes form a combination
of power control and ability of make up for deep fades.
|
1102.4086
|
Schroedinger Eigenmaps for the Analysis of Bio-Medical Data
|
cs.CE physics.data-an physics.med-ph q-bio.QM
|
We introduce Schroedinger Eigenmaps, a new semi-supervised manifold learning
and recovery technique. This method is based on an implementation of graph
Schroedinger operators with appropriately constructed barrier potentials as
carriers of labeled information. We use our approach for the analysis of
standard bio-medical datasets and new multispectral retinal images.
|
1102.4099
|
Capacity Achieving Linear Codes with Random Binary Sparse Generating
Matrices
|
cs.IT math.IT
|
In this paper, we prove the existence of capacity achieving linear codes with
random binary sparse generating matrices. The results on the existence of
capacity achieving linear codes in the literature are limited to the random
binary codes with equal probability generating matrix elements and sparse
parity-check matrices. Moreover, the codes with sparse generating matrices
reported in the literature are not proved to be capacity achieving.
As opposed to the existing results in the literature, which are based on
optimal maximum a posteriori decoders, the proposed approach is based on a
different decoder and consequently is suboptimal. We also demonstrate an
interesting trade-off between the sparsity of the generating matrix and the
error exponent (a constant which determines how exponentially fast the
probability of error decays as block length tends to infinity). An interesting
observation is that for small block sizes, less sparse generating matrices have
better performances while for large blok sizes, the performance of the random
generating matrices become independent of the sparsity. Moreover, we prove the
existence of capacity achieving linear codes with a given (arbitrarily low)
density of ones on rows of the generating matrix. In addition to proving the
existence of capacity achieving sparse codes, an important conclusion of our
paper is that for a sufficiently large code length, no search is necessary in
practice to find a deterministic matrix by proving that any arbitrarily
selected sequence of sparse generating matrices is capacity achieving with high
probability. The focus in this paper is on the binary symmetric and binary
erasure channels.her discrete memory-less symmetric channels.
|
1102.4104
|
Characterizing Discriminative Patterns
|
cs.DB cs.IT math.IT q-bio.GN
|
Discriminative patterns are association patterns that occur with
disproportionate frequency in some classes versus others, and have been studied
under names such as emerging patterns and contrast sets. Such patterns have
demonstrated considerable value for classification and subgroup discovery, but
a detailed understanding of the types of interactions among items in a
discriminative pattern is lacking. To address this issue, we propose to
categorize discriminative patterns according to four types of item interaction:
(i) driver-passenger, (ii) coherent, (iii) independent additive and (iv)
synergistic beyond independent additive. Either of the last three is of
practical importance, with the latter two representing a gain in the
discriminative power of a pattern over its subsets. Synergistic patterns are
most restrictive, but perhaps the most interesting since they capture a
cooperative effect. For domains such as genetic research, differentiating among
these types of patterns is critical since each yields very different biological
interpretations. For general domains, the characterization provides a novel
view of the nature of the discriminative patterns in a dataset, which yields
insights beyond those provided by current approaches that focus mostly on
pattern-based classification and subgroup discovery. This paper presents a
comprehensive discussion that defines these four pattern types and investigates
their properties and their relationship to one another. In addition, these
ideas are explored for a variety of datasets (ten UCI datasets, one gene
expression dataset and two genetic-variation datasets). The results demonstrate
the existence, characteristics and statistical significance of the different
types of patterns. They also illustrate how pattern characterization can
provide novel insights into discriminative pattern mining and the
discriminative structure of different datasets.
|
1102.4126
|
Multiuser Cognitive Radio Networks: An Information Theoretic Perspective
|
cs.IT math.IT
|
Achievable rate regions and outer bounds are derived for three-user
interference channels where the transmitters cooperate in a unidirectional
manner via a noncausal message-sharing mechanism. The three-user channel
facilitates different ways of message-sharing between the primary and secondary
(or cognitive) transmitters. Three natural extensions of unidirectional
message-sharing from two users to three users are introduced: (i) Cumulative
message sharing; (ii) primary-only message sharing; and (iii) cognitive-only
message sharing. To emphasize the notion of interference management, channels
are classified based on different rate-splitting strategies at the
transmitters. Standard techniques, superposition coding and Gel'fand-Pinsker's
binning principle, are employed to derive an achievable rate region for each of
the cognitive interference channels. Simulation results for the Gaussian
channel case are presented; they enable visual comparison of the achievable
rate regions for different message-sharing schemes along with the outer bounds.
These results also provide useful insights into the effect of rate-splitting at
the transmitters, which aids in better interference management at the
receivers.
|
1102.4132
|
Optimal dividend control for a generalized risk model with investment
incomes and debit interest
|
math.OC cs.SY q-fin.RM
|
This paper investigates dividend optimization of an insurance corporation
under a more realistic model which takes into consideration refinancing or
capital injections. The model follows the compound Poisson framework with
credit interest for positive reserve, and debit interest for negative reserve.
Ruin occurs when the reserve drops below the critical value. The company
controls the dividend pay-out dynamically with the objective to maximize the
expected total discounted dividends until ruin. We show that that the optimal
strategy is a band strategy and it is optimal to pay no dividends when the
reserve is negative.
|
1102.4135
|
Location Cheating: A Security Challenge to Location-based Social Network
Services
|
cs.SI cs.CR
|
Location-based mobile social network services such as foursquare and Gowalla
have grown exponentially over the past several years. These location-based
services utilize the geographical position to enrich user experiences in a
variety of contexts, including location-based searching and location-based
mobile advertising. To attract more users, the location-based mobile social
network services provide real-world rewards to the user, when a user checks in
at a certain venue or location. This gives incentives for users to cheat on
their locations. In this report, we investigate the threat of location cheating
attacks, find the root cause of the vulnerability, and outline the possible
defending mechanisms. We use foursquare as an example to introduce a novel
location cheating attack, which can easily pass the current location
verification mechanism (e.g., cheater code of foursquare). We also crawl the
foursquare website. By analyzing the crawled data, we show that automated large
scale cheating is possible. Through this work, we aim to call attention to
location cheating in mobile social network services and provide insights into
the defending mechanisms.
|
1102.4137
|
Using Distributed Rotations for a Low-Complexity Dynamic
Decode-and-Forward Relay Protocol
|
cs.IT math.IT
|
In this paper, we propose to implement the dynamic decode-and-forward (DDF)
protocol with distributed rotations. In addition to being the first
minimum-delay implementation of the DDF protocol proposed for any number of
relays, this technique allows to exploit cooperative diversity without inducing
the high decoding complexity of a space-time code. The analysis of outage
probabilities for different number of relays and rotations shows that the
performance of this technique is close to optimal. Moreover, a lower-bound on
the diversity-multiplexing gain tradeoff (DMT) is provided in the case of a
single relay and two rotations. This lower-bound reaches the optimal DDF's DMT
when the frame-length grows to infinity, which shows that even a small number
of rotations is enough to obtain good performance.
|
1102.4180
|
Characterizing and approximating eigenvalue sets of symmetric interval
matrices
|
cs.RO
|
We consider the eigenvalue problem for the case where the input matrix is
symmetric and its entries perturb in some given intervals. We present a
characterization of some of the exact boundary points, which allows us to
introduce an inner approximation algorithm, that in many case estimates exact
bounds. To our knowledge, this is the first algorithm that is able to guaran-
tee exactness. We illustrate our approach by several examples and numerical
experiments.
|
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