id
stringlengths 9
16
| title
stringlengths 4
278
| categories
stringlengths 5
104
| abstract
stringlengths 6
4.09k
|
|---|---|---|---|
0804.3120
|
The Capacity Of Two Way Relay Channel
|
cs.IT math.IT
|
This paper investigates the capacity of a wireless two way relay channel in
which two end nodes exchange information via a relay node. The capacity is
defined in the information-theoretic sense as the maximum information exchange
rate between the two end nodes. We give an upper bound of the capacity by
applying the cut-set theorem. We prove that this upper bound can be approached
in low SNR region using "separated" multiple access for uplinks from the end
nodes to the relay in which the data from the end nodes are individually
decoded at the relay; and network-coding broadcast for downlinks from the relay
to the end nodes in which the relay mixes the information from end nodes before
forwarding. We further prove that the capacity is approachable in high SNR
region using physical-layer network coding (PNC) multiple access for uplinks,
and network-coding broadcast for downlinks. From our proof and observations, we
conjecture that the upper bound may be achieved with PNC in all SNR regions.
|
0804.3155
|
Leveraging Coherent Distributed Space-Time Codes for Noncoherent
Communication in Relay Networks via Training
|
cs.IT math.IT
|
For point to point multiple input multiple output systems,
Dayal-Brehler-Varanasi have proved that training codes achieve the same
diversity order as that of the underlying coherent space time block code (STBC)
if a simple minimum mean squared error estimate of the channel formed using the
training part is employed for coherent detection of the underlying STBC. In
this letter, a similar strategy involving a combination of training, channel
estimation and detection in conjunction with existing coherent distributed
STBCs is proposed for noncoherent communication in AF relay networks.
Simulation results show that the proposed simple strategy outperforms
distributed differential space-time coding for AF relay networks. Finally, the
proposed strategy is extended to asynchronous relay networks using orthogonal
frequency division multiplexing.
|
0804.3160
|
On the performance of approximate equilibria in congestion games
|
cs.GT cs.AI cs.NI
|
We study the performance of approximate Nash equilibria for linear congestion
games. We consider how much the price of anarchy worsens and how much the price
of stability improves as a function of the approximation factor $\epsilon$. We
give (almost) tight upper and lower bounds for both the price of anarchy and
the price of stability for atomic and non-atomic congestion games. Our results
not only encompass and generalize the existing results of exact equilibria to
$\epsilon$-Nash equilibria, but they also provide a unified approach which
reveals the common threads of the atomic and non-atomic price of anarchy
results. By expanding the spectrum, we also cast the existing results in a new
light. For example, the Pigou network, which gives tight results for exact Nash
equilibria of selfish routing, remains tight for the price of stability of
$\epsilon$-Nash equilibria but not for the price of anarchy.
|
0804.3171
|
Optimization Approach for Detecting the Critical Data on a Database
|
cs.DB
|
Through purposeful introduction of malicious transactions (tracking
transactions) into randomly select nodes of a (database) graph, soiled and
clean segments are identified. Soiled and clean measures corresponding those
segments are then computed. These measures are used to repose the problem of
critical database elements detection as an optimization problem over the graph.
This method is universally applicable over a large class of graphs (including
directed, weighted, disconnected, cyclic) that occur in several contexts of
databases. A generalization argument is presented which extends the critical
data problem to abstract settings.
|
0804.3215
|
Multicast Capacity of Optical WDM Packet Ring for Hotspot Traffic
|
cs.IT math.IT
|
Packet-switching WDM ring networks with a hotspot transporting unicast,
multicast, and broadcast traffic are important components of high-speed
metropolitan area networks. For an arbitrary multicast fanout traffic model
with uniform, hotspot destination, and hotspot source packet traffic, we
analyze the maximum achievable long-run average packet throughput, which we
refer to as \textit{multicast capacity}, of bi-directional shortest-path routed
WDM rings. We identify three segments that can experience the maximum
utilization, and thus, limit the multicast capacity. We characterize the
segment utilization probabilities through bounds and approximations, which we
verify through simulations. We discover that shortest-path routing can lead to
utilization probabilities above one half for moderate to large portions of
hotspot source multi- and broadcast traffic, and consequently multicast
capacities of less than two simultaneous packet transmissions. We outline a
one-copy routing strategy that guarantees a multicast capacity of at least two
simultaneous packet transmissions for arbitrary hotspot source traffic.
|
0804.3234
|
Technical Report - Automatic Contour Extraction from 2D Neuron Images
|
cs.CV q-bio.NC
|
This work describes a novel methodology for automatic contour extraction from
2D images of 3D neurons (e.g. camera lucida images and other types of 2D
microscopy). Most contour-based shape analysis methods can not be used to
characterize such cells because of overlaps between neuronal processes. The
proposed framework is specifically aimed at the problem of contour following
even in presence of multiple overlaps. First, the input image is preprocessed
in order to obtain an 8-connected skeleton with one-pixel-wide branches, as
well as a set of critical regions (i.e., bifurcations and crossings). Next, for
each subtree, the tracking stage iteratively labels all valid pixel of
branches, up to a critical region, where it determines the suitable direction
to proceed. Finally, the labeled skeleton segments are followed in order to
yield the parametric contour of the neuronal shape under analysis. The reported
system was successfully tested with respect to several images and the results
from a set of three neuron images are presented here, each pertaining to a
different class, i.e. alpha, delta and epsilon ganglion cells, containing a
total of 34 crossings. The algorithms successfully got across all these
overlaps. The method has also been found to exhibit robustness even for images
with close parallel segments. The proposed method is robust and may be
implemented in an efficient manner. The introduction of this approach should
pave the way for more systematic application of contour-based shape analysis
methods in neuronal morphology.
|
0804.3255
|
Reconstruction of Multidimensional Signals from Irregular Noisy Samples
|
cs.IT math.IT
|
We focus on a multidimensional field with uncorrelated spectrum, and study
the quality of the reconstructed signal when the field samples are irregularly
spaced and affected by independent and identically distributed noise. More
specifically, we apply linear reconstruction techniques and take the mean
square error (MSE) of the field estimate as a metric to evaluate the signal
reconstruction quality. We find that the MSE analysis could be carried out by
using the closed-form expression of the eigenvalue distribution of the matrix
representing the sampling system. Unfortunately, such distribution is still
unknown. Thus, we first derive a closed-form expression of the distribution
moments, and we find that the eigenvalue distribution tends to the
Marcenko-Pastur distribution as the field dimension goes to infinity. Finally,
by using our approach, we derive a tight approximation to the MSE of the
reconstructed field.
|
0804.3259
|
On Multiuser Power Region of Fading Multiple-Access Channel with
Multiple Antennas
|
cs.IT math.IT
|
This paper is concerned with the fading MIMO-MAC with multiple receive
antennas at the base station (BS) and multiple transmit antennas at each mobile
terminal (MT). Two multiple-access techniques are considered for scheduling
transmissions from each MT to the BS at the same frequency, which are
space-division multiple-access (SDMA) and time-division multiple-access (TDMA).
For SDMA, all MTs transmit simultaneously to the BS and their individual
signals are resolved at the BS via multiple receive antennas while for TDMA,
each MT transmits independently to the BS during mutually orthogonal time
slots. It is assumed that the channel-state information (CSI) of the fading
channel from each MT to the BS is unknown at each MT transmitter, but is
perfectly known at the BS receiver. Thereby, the BS can acquire the long-term
channel-distribution information (CDI) for each MT. This paper extends the
well-known transmit-covariance feedback scheme for the point-to-point fading
MIMO channel to the fading MIMO-MAC, whereby the BS jointly optimizes the
transmit signal covariance matrices for all MTs based on their CDI, and then
sends each transmit covariance matrix back to the corresponding MT via a
feedback channel. The main goal of this paper is to characterize the so-called
multiuser power region under the multiuser transmit-covariance feedback scheme
for both SDMA and TDMA. The power region is defined as the constitution of all
user transmit power-tuples that can achieve reliable transmissions for a given
set of user target rates. Simulation results show that SDMA can achieve
substantial power savings over TDMA for the fading MIMO-MAC. Moreover, this
paper demonstrates the usefulness of the multiuser power region for maintaining
proportionally-fair power consumption among the MTs.
|
0804.3261
|
Optimal Dynamic Resource Allocation for Multi-Antenna Broadcasting with
Heterogeneous Delay-Constrained Traffic
|
cs.IT math.IT
|
This paper is concerned with dynamic resource allocation in a cellular
wireless network with slow fading for support of data traffic having
heterogeneous transmission delay requirements. The multiple-input single-output
(MISO) fading broadcast channel (BC) is of interest where the base station (BS)
employs multiple transmit antennas to realize simultaneous downlink
transmission at the same frequency to multiple mobile users each having a
single receive antenna. An information-theoretic approach is taken for
characterizing capacity limits of the fading MISO-BC under various transmission
delay considerations. First, this paper studies transmit optimization at the BS
when some users have delay-tolerant ``packet'' data and the others have
delay-sensitive ``circuit'' data for transmission at the same time. Based on
the convex optimization framework, an online resource allocation algorithm is
derived that is amenable to efficient cross-layer implementation of both
physical (PHY) -layer multi-antenna transmission and media-access-control (MAC)
-layer multiuser rate scheduling. Secondly, this paper investigates the
fundamental throughput-delay tradeoff for transmission over the fading MISO-BC.
By comparing the network throughput under completely relaxed versus strictly
zero transmission delay constraint, this paper characterizes the limiting loss
in sum capacity due to the vanishing delay tolerance, termed the delay penalty,
under some prescribed user fairness for transmit rate allocation.
|
0804.3269
|
Phoneme recognition in TIMIT with BLSTM-CTC
|
cs.CL cs.NE
|
We compare the performance of a recurrent neural network with the best
results published so far on phoneme recognition in the TIMIT database. These
published results have been obtained with a combination of classifiers.
However, in this paper we apply a single recurrent neural network to the same
task. Our recurrent neural network attains an error rate of 24.6%. This result
is not significantly different from that obtained by the other best methods,
but they rely on a combination of classifiers for achieving comparable
performance.
|
0804.3271
|
Information Theoretic Operating Regimes of Large Wireless Networks
|
cs.IT math.IT
|
In analyzing the point-to-point wireless channel, insights about two
qualitatively different operating regimes--bandwidth- and power-limited--have
proven indispensable in the design of good communication schemes. In this
paper, we propose a new scaling law formulation for wireless networks that
allows us to develop a theory that is analogous to the point-to-point case. We
identify fundamental operating regimes of wireless networks and derive
architectural guidelines for the design of optimal schemes.
Our analysis shows that in a given wireless network with arbitrary size,
area, power, bandwidth, etc., there are three parameters of importance: the
short-distance SNR, the long-distance SNR, and the power path loss exponent of
the environment. Depending on these parameters we identify four qualitatively
different regimes. One of these regimes is especially interesting since it is
fundamentally a consequence of the heterogeneous nature of links in a network
and does not occur in the point-to-point case; the network capacity is {\em
both} power and bandwidth limited. This regime has thus far remained hidden due
to the limitations of the existing formulation. Existing schemes, either
multihop transmission or hierarchical cooperation, fail to achieve capacity in
this regime; we propose a new hybrid scheme that achieves capacity.
|
0804.3361
|
A New Approach to Automated Epileptic Diagnosis Using EEG and
Probabilistic Neural Network
|
cs.AI cs.CV
|
Epilepsy is one of the most common neurological disorders that greatly impair
patient' daily lives. Traditional epileptic diagnosis relies on tedious visual
screening by neurologists from lengthy EEG recording that requires the presence
of seizure (ictal) activities. Nowadays, there are many systems helping the
neurologists to quickly find interesting segments of the lengthy signal by
automatic seizure detection. However, we notice that it is very difficult, if
not impossible, to obtain long-term EEG data with seizure activities for
epilepsy patients in areas lack of medical resources and trained neurologists.
Therefore, we propose to study automated epileptic diagnosis using interictal
EEG data that is much easier to collect than ictal data. The authors are not
aware of any report on automated EEG diagnostic system that can accurately
distinguish patients' interictal EEG from the EEG of normal people. The
research presented in this paper, therefore, aims to develop an automated
diagnostic system that can use interictal EEG data to diagnose whether the
person is epileptic. Such a system should also detect seizure activities for
further investigation by doctors and potential patient monitoring. To develop
such a system, we extract four classes of features from the EEG data and build
a Probabilistic Neural Network (PNN) fed with these features. Leave-one-out
cross-validation (LOO-CV) on a widely used epileptic-normal data set reflects
an impressive 99.5% accuracy of our system on distinguishing normal people's
EEG from patient's interictal EEG. We also find our system can be used in
patient monitoring (seizure detection) and seizure focus localization, with
96.7% and 77.5% accuracy respectively on the data set.
|
0804.3421
|
Coalitions in Cooperative Wireless Networks
|
cs.GT cs.IT math.IT
|
Cooperation between rational users in wireless networks is studied using
coalitional game theory. Using the rate achieved by a user as its utility, it
is shown that the stable coalition structure, i.e., set of coalitions from
which users have no incentives to defect, depends on the manner in which the
rate gains are apportioned among the cooperating users. Specifically, the
stability of the grand coalition (GC), i.e., the coalition of all users, is
studied. Transmitter and receiver cooperation in an interference channel (IC)
are studied as illustrative cooperative models to determine the stable
coalitions for both flexible (transferable) and fixed (non-transferable)
apportioning schemes. It is shown that the stable sum-rate optimal coalition
when only receivers cooperate by jointly decoding (transferable) is the GC. The
stability of the GC depends on the detector when receivers cooperate using
linear multiuser detectors (non-transferable). Transmitter cooperation is
studied assuming that all receivers cooperate perfectly and that users outside
a coalition act as jammers. The stability of the GC is studied for both the
case of perfectly cooperating transmitters (transferrable) and under a partial
decode-and-forward strategy (non-transferable). In both cases, the stability is
shown to depend on the channel gains and the transmitter jamming strengths.
|
0804.3430
|
Combining Beamforming and Space-Time Coding Using Noisy Quantized
Feedback
|
cs.IT math.IT
|
The goal of combining beamforming and space-time coding in this work is to
obtain full-diversity order and to provide additional received power (array
gain) compared to conventional space-time codes. In our system, we consider a
quasi-static fading environment and we incorporate both high-rate and low-rate
feedback channels with possible feedback errors. To utilize feedback
information, a class of code constellations is proposed, inspired from
orthogonal designs and precoded space-time block codes, which is called
generalized partly orthogonal designs or generalized PODs. Furthermore, to
model feedback errors, we assume that the feedback bits go through binary
symmetric channels (BSCs). Two cases are studied: first, when the BSC bit error
probability is known a priori to the transmission ends and second, when it is
not known exactly. In the first case, we derive a minimum pairwise error
probability (PEP) design criterion for generalized PODs. Then we design the
quantizer for the erroneous feedback channel and the precoder codebook of PODs
based on this criterion. The quantization scheme in our system is a channel
optimized vector quantizer (COVQ). In the second case, the design of the
quantizer and the precoder codebook is based on similar approaches, however
with a worst-case design strategy. The attractive property of our combining
scheme is that it converges to conventional space-time coding with low-rate and
erroneous feedback and to directional beamforming with high-rate and error-free
feedback. This scheme shows desirable robustness against feedback channel
modeling mismatch.
|
0804.3439
|
Information theoretic bounds for Compressed Sensing
|
cs.IT math.IT
|
In this paper we derive information theoretic performance bounds to sensing
and reconstruction of sparse phenomena from noisy projections. We consider two
settings: output noise models where the noise enters after the projection and
input noise models where the noise enters before the projection. We consider
two types of distortion for reconstruction: support errors and mean-squared
errors. Our goal is to relate the number of measurements, $m$, and $\snr$, to
signal sparsity, $k$, distortion level, $d$, and signal dimension, $n$. We
consider support errors in a worst-case setting. We employ different variations
of Fano's inequality to derive necessary conditions on the number of
measurements and $\snr$ required for exact reconstruction. To derive sufficient
conditions we develop new insights on max-likelihood analysis based on a novel
superposition property. In particular this property implies that small support
errors are the dominant error events. Consequently, our ML analysis does not
suffer the conservatism of the union bound and leads to a tighter analysis of
max-likelihood. These results provide order-wise tight bounds. For output noise
models we show that asymptotically an $\snr$ of $\Theta(\log(n))$ together with
$\Theta(k \log(n/k))$ measurements is necessary and sufficient for exact
support recovery. Furthermore, if a small fraction of support errors can be
tolerated, a constant $\snr$ turns out to be sufficient in the linear sparsity
regime. In contrast for input noise models we show that support recovery fails
if the number of measurements scales as $o(n\log(n)/SNR)$ implying poor
compression performance for such cases. We also consider Bayesian set-up and
characterize tradeoffs between mean-squared distortion and the number of
measurements using rate-distortion theory.
|
0804.3453
|
Weighted Sum Rate Optimization for Cognitive Radio MIMO Broadcast
Channels
|
cs.IT math.IT
|
In this paper, we consider a cognitive radio (CR) network in which the
unlicensed (secondary) users are allowed to concurrently access the spectrum
allocated to the licensed (primary) users provided that their interference to
the primary users (PUs) satisfies certain constraints. We study a weighted sum
rate maximization problem for the secondary user (SU) multiple input multiple
output (MIMO) broadcast channel (BC), in which the SUs have not only the sum
power constraint but also interference constraints. We first transform this
multi-constraint maximization problem into its equivalent form, which involves
a single constraint with multiple auxiliary variables. Fixing these multiple
auxiliary variables, we propose a duality result for the equivalent problem.
Our duality result can solve the optimization problem for MIMO-BC with multiple
linear constraints, and thus can be viewed as an extension of the conventional
results, which rely crucially on a single sum power constraint. Furthermore, we
develop an efficient sub-gradient based iterative algorithm to solve the
equivalent problem and show that the developed algorithm converges to a
globally optimal solution. Simulation results are further provided to
corroborate the effectiveness of the proposed algorithm.
|
0804.3459
|
Towards a stable definition of Kolmogorov-Chaitin complexity
|
cs.IT cs.CC math.IT
|
Although information content is invariant up to an additive constant, the
range of possible additive constants applicable to programming languages is so
large that in practice it plays a major role in the actual evaluation of K(s),
the Kolmogorov-Chaitin complexity of a string s. Some attempts have been made
to arrive at a framework stable enough for a concrete definition of K,
independent of any constant under a programming language, by appealing to the
"naturalness" of the language in question. The aim of this paper is to present
an approach to overcome the problem by looking at a set of models of
computation converging in output probability distribution such that that
"naturalness" can be inferred, thereby providing a framework for a stable
definition of K under the set of convergent models of computation.
|
0804.3500
|
Natural pseudo-distance and optimal matching between reduced size
functions
|
cs.CG cs.CV
|
This paper studies the properties of a new lower bound for the natural
pseudo-distance. The natural pseudo-distance is a dissimilarity measure between
shapes, where a shape is viewed as a topological space endowed with a
real-valued continuous function. Measuring dissimilarity amounts to minimizing
the change in the functions due to the application of homeomorphisms between
topological spaces, with respect to the $L_\infty$-norm. In order to obtain the
lower bound, a suitable metric between size functions, called matching
distance, is introduced. It compares size functions by solving an optimal
matching problem between countable point sets. The matching distance is shown
to be resistant to perturbations, implying that it is always smaller than the
natural pseudo-distance. We also prove that the lower bound so obtained is
sharp and cannot be improved by any other distance between size functions.
|
0804.3507
|
Sixteen New Linear Codes With Plotkin Sum
|
cs.IT math.IT
|
Sixteen new linear codes are presented: three of them improve the lower
bounds on the minimum distance for a linear code and the rest are an explicit
construction of unknown codes attaining the lower bounds on the minimum
distance. They are constructed using the Plotkin sum of two linear codes, also
called $(u|u+v)$ construction. The computations have been achieved using an
exhaustiv search.
|
0804.3575
|
Isotropic PCA and Affine-Invariant Clustering
|
cs.LG cs.CG
|
We present a new algorithm for clustering points in R^n. The key property of
the algorithm is that it is affine-invariant, i.e., it produces the same
partition for any affine transformation of the input. It has strong guarantees
when the input is drawn from a mixture model. For a mixture of two arbitrary
Gaussians, the algorithm correctly classifies the sample assuming only that the
two components are separable by a hyperplane, i.e., there exists a halfspace
that contains most of one Gaussian and almost none of the other in probability
mass. This is nearly the best possible, improving known results substantially.
For k > 2 components, the algorithm requires only that there be some
(k-1)-dimensional subspace in which the emoverlap in every direction is small.
Here we define overlap to be the ratio of the following two quantities: 1) the
average squared distance between a point and the mean of its component, and 2)
the average squared distance between a point and the mean of the mixture. The
main result may also be stated in the language of linear discriminant analysis:
if the standard Fisher discriminant is small enough, labels are not needed to
estimate the optimal subspace for projection. Our main tools are isotropic
transformation, spectral projection and a simple reweighting technique. We call
this combination isotropic PCA.
|
0804.3599
|
Respect My Authority! HITS Without Hyperlinks, Utilizing Cluster-Based
Language Models
|
cs.IR cs.CL
|
We present an approach to improving the precision of an initial document
ranking wherein we utilize cluster information within a graph-based framework.
The main idea is to perform re-ranking based on centrality within bipartite
graphs of documents (on one side) and clusters (on the other side), on the
premise that these are mutually reinforcing entities. Links between entities
are created via consideration of language models induced from them.
We find that our cluster-document graphs give rise to much better retrieval
performance than previously proposed document-only graphs do. For example,
authority-based re-ranking of documents via a HITS-style cluster-based approach
outperforms a previously-proposed PageRank-inspired algorithm applied to
solely-document graphs. Moreover, we also show that computing authority scores
for clusters constitutes an effective method for identifying clusters
containing a large percentage of relevant documents.
|
0804.3671
|
Constructions for Clumps Statistics
|
cs.DM cs.IR
|
We consider a component of the word statistics known as clump; starting from
a finite set of words, clumps are maximal overlapping sets of these
occurrences. This parameter has first been studied by Schbath with the aim of
counting the number of occurrences of words in random texts. Later work with
similar probabilistic approach used the Chen-Stein approximation for a compound
Poisson distribution, where the number of clumps follows a law close to
Poisson. Presently there is no combinatorial counterpart to this approach, and
we fill the gap here. We emphasize the fact that, in contrast with the
probabilistic approach which only provides asymptotic results, the
combinatorial approach provides exact results that are useful when considering
short sequences.
|
0804.3678
|
Causal inference using the algorithmic Markov condition
|
math.ST cs.IT math.IT stat.ML stat.TH
|
Inferring the causal structure that links n observables is usually based upon
detecting statistical dependences and choosing simple graphs that make the
joint measure Markovian. Here we argue why causal inference is also possible
when only single observations are present.
We develop a theory how to generate causal graphs explaining similarities
between single objects. To this end, we replace the notion of conditional
stochastic independence in the causal Markov condition with the vanishing of
conditional algorithmic mutual information and describe the corresponding
causal inference rules.
We explain why a consistent reformulation of causal inference in terms of
algorithmic complexity implies a new inference principle that takes into
account also the complexity of conditional probability densities, making it
possible to select among Markov equivalent causal graphs. This insight provides
a theoretical foundation of a heuristic principle proposed in earlier work.
We also discuss how to replace Kolmogorov complexity with decidable
complexity criteria. This can be seen as an algorithmic analog of replacing the
empirically undecidable question of statistical independence with practical
independence tests that are based on implicit or explicit assumptions on the
underlying distribution.
|
0804.3680
|
Word-Based Text Compression
|
cs.IT math.IT
|
Today there are many universal compression algorithms, but in most cases is
for specific data better using specific algorithm - JPEG for images, MPEG for
movies, etc. For textual documents there are special methods based on PPM
algorithm or methods with non-character access, e.g. word-based compression. In
the past, several papers describing variants of word-based compression using
Huffman encoding or LZW method were published. The subject of this paper is the
description of a word-based compression variant based on the LZ77 algorithm.
The LZ77 algorithm and its modifications are described in this paper. Moreover,
various ways of sliding window implementation and various possibilities of
output encoding are described, as well. This paper also includes the
implementation of an experimental application, testing of its efficiency and
finding the best combination of all parts of the LZ77 coder. This is done to
achieve the best compression ratio. In conclusion there is comparison of this
implemented application with other word-based compression programs and with
other commonly used compression programs.
|
0804.3817
|
Multiple Random Oracles Are Better Than One
|
cs.LG
|
We study the problem of learning k-juntas given access to examples drawn from
a number of different product distributions. Thus we wish to learn a function f
: {-1,1}^n -> {-1,1} that depends on k (unknown) coordinates. While the best
known algorithms for the general problem of learning a k-junta require running
time of n^k * poly(n,2^k), we show that given access to k different product
distributions with biases separated by \gamma>0, the functions may be learned
in time poly(n,2^k,\gamma^{-k}). More generally, given access to t <= k
different product distributions, the functions may be learned in time n^{k/t} *
poly(n,2^k,\gamma^{-k}). Our techniques involve novel results in Fourier
analysis relating Fourier expansions with respect to different biases and a
generalization of Russo's formula.
|
0804.3825
|
On the inner and outer bounds for 2-receiver discrete memoryless
broadcast channels
|
cs.IT math.IT
|
We study the best known general inner bound[MAR '79] and outer bound[N-EG'07]
for the capacity region of the two user discrete memory less channel. We prove
that a seemingly stronger outer bound is identical to a weaker form of the
outer bound that was also presented in [N-EG'07]. We are able to further
express the best outer bound in a form that is computable, i.e. there are
bounds on the cardinalities of the auxiliary random variables.
The inner and outer bounds coincide for all channels for which the capacity
region is known and it is not known whether the regions described by these
bounds are same or different. We present a channel, where assuming a certain
conjecture backed by simulations and partial theoretical results, one can show
that the bounds are different.
|
0804.3862
|
Image Processing in Optical Guidance for Autonomous Landing of Lunar
Probe
|
cs.RO
|
Because of the communication delay between earth and moon, the GNC technology
of lunar probe is becoming more important than ever. Current navigation
technology is not able to provide precise motion estimation for probe landing
control system Computer vision offers a new approach to solve this problem. In
this paper, author introduces an image process algorithm of computer vision
navigation for autonomous landing of lunar probe. The purpose of the algorithm
is to detect and track feature points which are factors of navigation. Firstly,
fixation areas are detected as sub-images and matched. Secondly, feature points
are extracted from sub-images and tracked. Computer simulation demonstrates the
result of algorithm takes less computation and fulfils requests of navigation
algorithm.
|
0804.3868
|
Comparison of Various Methods for the Calculation of the Distance
Potential Field
|
physics.comp-ph cs.MA physics.soc-ph
|
The distance from a given position toward one or more destinations, exits,
and way points is a more or less important input variable in most models of
pedestrian dynamics. Except for the special case when there are no obstacles in
a concave scenario -- i.e. each position is visible from any other -- the
calculation of these distances is a non-trivial task. This isn't that big a
problem, as long as the model only demands the distances to be stored in a
Static Floor Field also called Potential Field, which never changes throughout
the whole simulation. In this case a pre-calculation once before the simulation
starts is sufficient. But if one wants to allow changes of the geometry during
a simulation run -- imagine doors or the blocking of a corridor due to some
hazard -- in the Distance Potential Field, calculation time matters strongly.
This contribution gives an overview over existing and new exact and approximate
methods to calculate a potential field, analytical investigations for their
exactness, and tests of their computation speed. The advantages and drawbacks
of the methods are discussed.
|
0804.3874
|
Hardware In The Loop Simulator in UAV Rapid Development Life Cycle
|
cs.RO
|
Field trial is very critical and high risk in autonomous UAV development life
cycle. Hardware in the loop (HIL) simulation is a computer simulation that has
the ability to simulate UAV flight characteristic, sensor modeling and actuator
modeling while communicating in real time with the UAV autopilot hardware. HIL
simulation can be used to test the UAV autopilot hardware reliability, test the
closed loop performance of the overall system and tuning the control parameter.
By rigorous testing in the HIL simulator, the risk in the field trial can be
minimized.
|
0804.3879
|
Effects of Leaders Position and Shape on Aerodynamic Performances of V
Flight Formation
|
cs.RO
|
The influences of the leader in a group of V flight formation are dealt with.
The investigation is focused on the effect of its position and shape on
aerodynamics performances of a given V flight formation. Vortices generated the
wing tip of the leader moves downstream forming a pair of opposite rotating
line vortices. These vortices are generally undesirable because they create a
downwash that increases the induced drag on leaders wing. However, this
downwash is also accompanied by an upwash that can beneficial to the followers
wing flying behind the leaders one, namely a favorable lift for the followers
wing. How much contributions of the leaders wing to the followers wing in the V
formation flight is determined by the strength of tip vortices generated by the
leaders wing which is influenced by its position and shape including incidence
angle, dihedral angle, aspect ratio and taper ratio. The prediction of
aerodynamic performances of the V flight formation including lift, drag and
moment coefficients is numerically performed by solving Navier Stokes equations
with k e turbulence model. The computational domain is defined with multiblock
topology to capture the complex geometry arrangement of the V flight formation.
|
0804.3881
|
Automated Flight Test and System Identification for Rotary Wing Small
Aerial Platform using Frequency Responses Analysis
|
cs.RO
|
This paper proposes an autopilot system that can be used to control the small
scale rotorcraft during the flight test for linear-frequency-domain system
identification. The input frequency swept is generated automatically as part of
the autopilot control command. Therefore the bandwidth coverage and consistency
of the frequency swept is guaranteed to produce high quality data for system
identification. Beside that we can set the safety parameter during the flight
test (maximum roll or pitch value, minimum altitude, etc) so the safety of the
whole flight test is guaranteed. This autopilot for automated flight test will
be tested using hardware in the loop simulator for hover flight condition.
|
0804.3882
|
Virtual Reality Simulation of Fire Fighting Robot Dynamic and Motion
|
cs.RO
|
This paper presents one approach in designing a Fire Fighting Robot which has
been contested annually in a robotic student competition in many countries
following the rules initiated at the Trinity College. The approach makes use of
computer simulation and animation in a virtual reality environment. In the
simulation, the amount of time, starting from home until the flame is
destroyed, can be confirmed. The efficacy of algorithms and parameter values
employed can be easily evaluated. Rather than spending time building the real
robot in a trial and error fashion, now students can explore more variation of
algorithm, parameter and sensor-actuator configuration in the early stage of
design. Besides providing additional excitement during learning process and
enhancing students understanding to the engineering aspects of the design, this
approach could become a useful tool to increase the chance of winning the
contest.
|
0804.3885
|
Heading Lock Maneuver Testing of Autonomous Underwater Vehicle
|
cs.RO
|
In recent years, Autonomous Underwater Vehicle (UAV) research and development
at Bandung Institute of Technology in Indonesia has achieved the testing stage
in the field. This testing was still being classified as the early testing,
since some of the preliminary tests were carried out in the scale of the
laboratory. The paper would discuss the laboratory test and several tests that
were done in the field. Discussions were stressed in the procedure and the aim
that will be achieved, along with several early results. The testing was
carried out in the lake with the area around 8300 Ha and the maximum depth of
50 meters. The location of the testing was chosen with consideration of
minimizing the effect of the current and the wave, as well as the location that
was not too far from the Laboratory. The type of testing that will be discussed
in paper was Heading Lock Maneuver Testing. The vehicle was tested to move with
a certain cruising speed, afterwards it was commanded by an arbitrarily
selected heading direction. The response and the behavior of the vehicle were
recorded as the data produced by the testing.
|
0804.3891
|
Development of Architectures for Internet Telerobotics Systems
|
cs.RO
|
This paper presents our experience in developing and implementing Internet
telerobotics system. Internet telerobotics system refers to a robot system
controlled and monitored remotely through the Internet. A robot manipulator
with five degrees of freedom, called Mentor, is employed. Client-server
architecture is chosen as a platform for our Internet telerobotics system.
Three generations of telerobotics systems have evolved in this research. The
first generation was based on CGI and two tiered architecture, where a client
presents a Graphical User Interface to the user, and utilizes the user's data
entry and actions to perform requests to robot server running on a different
machine. The second generation was developed using Java. We also employ Java 3D
for creating and manipulating 3D geometry of manipulator links and for
constructing the structures used in rendering that geometry, resulting in 3D
robot movement simulation presented to the users(clients) through their web
browser. Recent development in our Internet telerobotics includes object
recognition through image captured by a camera, which poses challenging
problem, given the undeterministic latency of the Internet. The third
generation is centered around the use of CORBA for development platform of
distributed internet telerobotics system, aimed at distributing task of
telerobotics system.
|
0804.3894
|
Unmanned Aerial Vehicle Instrumentation for Rapid Aerial Photo System
|
cs.RO
|
This research will proposed a new kind of relatively low cost autonomous UAV
that will enable farmers to make just in time mosaics of aerial photo of their
crop. These mosaics of aerial photo should be able to be produced with
relatively low cost and within the 24 hours of acquisition constraint. The
autonomous UAV will be equipped with payload management system specifically
developed for rapid aerial mapping. As mentioned before turn around time is the
key factor, so accuracy is not the main focus (not orthorectified aerial
mapping). This system will also be equipped with special software to post
process the aerial photos to produce the mosaic aerial photo map
|
0804.3895
|
First Principle Approach to Modeling of Small Scale Helicopter
|
cs.RO
|
The establishment of global helicopter linear model is very precious and
useful for the design of the linear control laws, since it is never afforded in
the published literatures. In the first principle approach, the mathematical
model was developed using basic helicopter theory accounting for particular
characteristic of the miniature helicopter. No formal system identification
procedures are required for the proposed model structure. The relevant
published literatures however did not present the linear models required for
the design of linear control laws. The paper presents a step by step
development of linear model for small scale helicopter based on first-principle
approach. Beyond the previous work in literatures, the calculation of the
stability derivatives is presented in detail. A computer program is used to
solve the equilibrium conditions and then calculate the change in aerodynamics
forces and moments due to the change in each degree of freedom and control
input. The detail derivation allows the comprehensive analysis of relative
dominance of vehicle states and input variables to force and moment components.
Hence it facilitates the development of minimum complexity small scale
helicopter dynamics model.
|
0804.3897
|
Optimal Tracking Controller Design for a Small Scale Helicopter
|
cs.RO
|
A model helicopter is more difficult to control than its full scale
counterparts. This is due to its greater sensitivity to control inputs and
disturbances as well as higher bandwidth of dynamics. This works is focused on
designing practical tracking controller for a small scale helicopter following
predefined trajectories. A tracking controller based on optimal control theory
is synthesized as part of the development of an autonomous helicopter. Some
issues in regards to control constraints are addressed. The weighting between
state tracking performance and control power expenditure is analyzed. Overall
performance of the control design is evaluated based on its time domain
histories of trajectories as well as control inputs.
|
0804.4042
|
Uncorrectable Errors of Weight Half the Minimum Distance for Binary
Linear Codes
|
cs.IT math.IT
|
A lower bound on the number of uncorrectable errors of weight half the
minimum distance is derived for binary linear codes satisfying some condition.
The condition is satisfied by some primitive BCH codes, extended primitive BCH
codes, Reed-Muller codes, and random linear codes. The bound asymptotically
coincides with the corresponding upper bound for Reed-Muller codes and random
linear codes. By generalizing the idea of the lower bound, a lower bound on the
number of uncorrectable errors for weights larger than half the minimum
distance is also obtained, but the generalized lower bound is weak for large
weights. The monotone error structure and its related notion larger half and
trial set, which are introduced by Helleseth, Kl{\o}ve, and Levenshtein, are
mainly used to derive the bounds.
|
0804.4071
|
Logic Mining Using Neural Networks
|
cs.LO cs.NE
|
Knowledge could be gained from experts, specialists in the area of interest,
or it can be gained by induction from sets of data. Automatic induction of
knowledge from data sets, usually stored in large databases, is called data
mining. Data mining methods are important in the management of complex systems.
There are many technologies available to data mining practitioners, including
Artificial Neural Networks, Regression, and Decision Trees. Neural networks
have been successfully applied in wide range of supervised and unsupervised
learning applications. Neural network methods are not commonly used for data
mining tasks, because they often produce incomprehensible models, and require
long training times. One way in which the collective properties of a neural
network may be used to implement a computational task is by way of the concept
of energy minimization. The Hopfield network is well-known example of such an
approach. The Hopfield network is useful as content addressable memory or an
analog computer for solving combinatorial-type optimization problems. Wan
Abdullah [1] proposed a method of doing logic programming on a Hopfield neural
network. Optimization of logical inconsistency is carried out by the network
after the connection strengths are defined from the logic program; the network
relaxes to neural states corresponding to a valid interpretation. In this
article, we describe how Hopfield network is able to induce logical rules from
large database by using reverse analysis method: given the values of the
connections of a network, we can hope to know what logical rules are entrenched
in the database.
|
0804.4073
|
Grainy Numbers
|
cs.LO cs.AI
|
Grainy numbers are defined as tuples of bits. They form a lattice where the
meet and the join operations are an addition and a multiplication. They may be
substituted for the real numbers in the definition of fuzzy sets. The aim is to
propose an alternative negation for the complement that we'll call supplement.
|
0804.4075
|
Logic Learning in Hopfield Networks
|
cs.LO cs.NE
|
Synaptic weights for neurons in logic programming can be calculated either by
using Hebbian learning or by Wan Abdullah's method. In other words, Hebbian
learning for governing events corresponding to some respective program clauses
is equivalent with learning using Wan Abdullah's method for the same respective
program clauses. In this paper we will evaluate experimentally the equivalence
between these two types of learning through computer simulations.
|
0804.4187
|
On the Asymptotic Behavior of Selfish Transmitters Sharing a Common
Channel
|
cs.IT cs.GT math.IT
|
This paper analyzes the asymptotic behavior of a multiple-access network
comprising a large number of selfish transmitters competing for access to a
common wireless communication channel, and having different utility functions
for determining their strategies. A necessary and sufficient condition is given
for the total number of packet arrivals from selfish transmitters to converge
in distribution. The asymptotic packet arrival distribution at Nash equilibrium
is shown to be a mixture of a Poisson distribution and finitely many Bernoulli
distributions.
|
0804.4194
|
Asymptotic Bound on Binary Self-Orthogonal Codes
|
cs.IT math.IT
|
We present two constructions for binary self-orthogonal codes. It turns out
that our constructions yield a constructive bound on binary self-orthogonal
codes. In particular, when the information rate R=1/2, by our constructive
lower bound, the relative minimum distance \delta\approx 0.0595 (for GV bound,
\delta\approx 0.110). Moreover, we have proved that the binary self-orthogonal
codes asymptotically achieve the Gilbert-Varshamov bound.
|
0804.4195
|
Multi-Antenna Gaussian Broadcast Channels with Confidential Messages
|
cs.IT cs.CR math.IT
|
In wireless data networks, communication is particularly susceptible to
eavesdropping due to its broadcast nature. Security and privacy systems have
become critical for wireless providers and enterprise networks. This paper
considers the problem of secret communication over a Gaussian broadcast
channel, where a multi-antenna transmitter sends independent confidential
messages to two users with \emph{information-theoretic secrecy}. That is, each
user would like to obtain its own confidential message in a reliable and safe
manner. This communication model is referred to as the multi-antenna Gaussian
broadcast channel with confidential messages (MGBC-CM). Under this
communication scenario, a secret dirty-paper coding scheme and the
corresponding achievable secrecy rate region are first developed based on
Gaussian codebooks. Next, a computable Sato-type outer bound on the secrecy
capacity region is provided for the MGBC-CM. Furthermore, the Sato-type outer
bound proves to be consistent with the boundary of the secret dirty-paper
coding achievable rate region, and hence, the secrecy capacity region of the
MGBC-CM is established. Finally, a numerical example demonstrates that both
users can achieve positive rates simultaneously under the information-theoretic
secrecy requirement.
|
0804.4204
|
Distance Distributions in Finite Uniformly Random Networks: Theory and
Applications
|
cs.IT math.IT
|
In wireless networks, the knowledge of nodal distances is essential for
several areas such as system configuration, performance analysis and protocol
design. In order to evaluate distance distributions in random networks, the
underlying nodal arrangement is almost universally taken to be an infinite
Poisson point process. While this assumption is valid in some cases, there are
also certain impracticalities to this model. For example, practical networks
are non-stationary, and the number of nodes in disjoint areas are not
independent. This paper considers a more realistic network model where a finite
number of nodes are uniformly randomly distributed in a general d-dimensional
ball of radius R and characterizes the distribution of Euclidean distances in
the system. The key result is that the probability density function of the
distance from the center of the network to its nth nearest neighbor follows a
generalized beta distribution. This finding is applied to study network
characteristics such as energy consumption, interference, outage and
connectivity.
|
0804.4237
|
Explaining the Logical Nature of Electrical Solitons in Neural Circuits
|
cs.NE q-bio.NC
|
Neurons are modeled electrically based on ferroelectric membranes thin enough
to permit charge transfer, conjectured to be the tunneling result of thermally
energetic ions and random electrons. These membranes can be triggered to
produce electrical solitons, the main signals for brain associative memory and
logical processing. Dendritic circuits are modeled, and electrical solitons are
simulated to demonstrate the nature of soliton propagation, soliton reflection,
the collision of solitons, as well as soliton OR gates, AND gates, XOR gates
and NOT gates.
|
0804.4239
|
Capacity Definitions for General Channels with Receiver Side Information
|
cs.IT math.IT
|
We consider three capacity definitions for general channels with channel side
information at the receiver, where the channel is modeled as a sequence of
finite dimensional conditional distributions not necessarily stationary,
ergodic, or information stable. The {\em Shannon capacity} is the highest rate
asymptotically achievable with arbitrarily small error probability. The {\em
capacity versus outage} is the highest rate asymptotically achievable with a
given probability of decoder-recognized outage. The {\em expected capacity} is
the highest average rate asymptotically achievable with a single encoder and
multiple decoders, where the channel side information determines the decoder in
use. As a special case of channel codes for expected rate, the code for
capacity versus outage has two decoders: one operates in the non-outage states
and decodes all transmitted information, and the other operates in the outage
states and decodes nothing. Expected capacity equals Shannon capacity for
channels governed by a stationary ergodic random process but is typically
greater for general channels. These alternative capacity definitions
essentially relax the constraint that all transmitted information must be
decoded at the receiver. We derive capacity theorems for these capacity
definitions through information density. Numerical examples are provided to
demonstrate their connections and differences. We also discuss the implication
of these alternative capacity definitions for end-to-end distortion,
source-channel coding and separation.
|
0804.4255
|
Expected Message Delivery Time for Small-world Networks in the Continuum
Limit
|
cs.IT math.IT
|
Small-world networks are networks in which the graphical diameter of the
network is as small as the diameter of random graphs but whose nodes are highly
clustered when compared with the ones in a random graph. Examples of
small-world networks abound in sociology, biology, neuroscience and physics as
well as in human-made networks. This paper analyzes the average delivery time
of messages in dense small-world networks constructed on a plane. Iterative
equations for the average message delivery time in these networks are provided
for the situation in which nodes employ a simple greedy geographic routing
algorithm. It is shown that two network nodes communicate with each other only
through their short-range contacts, and that the average message delivery time
rises linearly if the separation between them is small. On the other hand, if
their separation increases, the average message delivery time rapidly saturates
to a constant value and stays almost the same for all large values of their
separation.
|
0804.4284
|
Network Coding Capacity of Random Wireless Networks under a SINR Model
|
cs.IT cs.NI math.IT
|
Previous work on network coding capacity for random wired and wireless
networks have focused on the case where the capacities of links in the network
are independent. In this paper, we consider a more realistic model, where
wireless networks are modelled by random geometric graphs with interference and
noise. In this model, the capacities of links are not independent. By employing
coupling and martingale methods, we show that, under mild conditions, the
network coding capacity for random wireless networks still exhibits a
concentration behavior around the mean value of the minimum cut.
|
0804.4298
|
Wireless Erasure Networks with Feedback
|
cs.IT math.IT
|
Consider a lossy packet network of queues, communicating over a wireless
medium. This paper presents a throughput-optimal transmission strategy for a
unicast network when feedback is available, which has the following advantages:
It requires a very limited form of acknowledgment feedback. It is completely
distributed, and independent of the network topology. Finally, communication at
the information theoretic cut-set rate requires no network coding and no
rateless coding on the packets. This simple strategy consists of each node
randomly choosing a packet from its buffer to transmit at each opportunity.
However, the packet is only deleted from a node's buffer once it has been
successfully received by the final destination
|
0804.4305
|
An Algorigtm for Singular Value Decomposition of Matrices in Blocks
|
math.NA cs.IR math.AC
|
Two methods to decompose block matrices analogous to Singular Matrix
Decomposition are proposed, one yielding the so called economy decomposition,
and other yielding the full decomposition. This method is devised to avoid
handling matrices bigger than the biggest blocks, so it is particularly
appropriate when a limitation on the size of matrices exists. The method is
tested on a document-term matrix (17780x3204) divided in 4 blocks, the
upper-left corner being 215x215.
|
0804.4316
|
Asymmetric Quantum LDPC Codes
|
quant-ph cs.IT math.IT
|
Recently, quantum error-correcting codes were proposed that capitalize on the
fact that many physical error models lead to a significant asymmetry between
the probabilities for bit flip and phase flip errors. An example for a channel
which exhibits such asymmetry is the combined amplitude damping and dephasing
channel, where the probabilities of bit flips and phase flips can be related to
relaxation and dephasing time, respectively. We give systematic constructions
of asymmetric quantum stabilizer codes that exploit this asymmetry. Our
approach is based on a CSS construction that combines BCH and finite geometry
LDPC codes.
|
0804.4336
|
Counterflow Extension for the F.A.S.T.-Model
|
cs.MA physics.comp-ph
|
The F.A.S.T. (Floor field and Agent based Simulation Tool) model is a
microscopic model of pedestrian dynamics, which is discrete in space and time.
It was developed in a number of more or less consecutive steps from a simple CA
model. This contribution is a summary of a study on an extension of the
F.A.S.T-model for counterflow situations. The extensions will be explained and
it will be shown that the extended F.A.S.T.-model is capable of handling
various counterflow situations and to reproduce the well known lane formation
effect.
|
0804.4384
|
Linear-Programming Decoding of Nonbinary Linear Codes
|
cs.IT math.IT
|
A framework for linear-programming (LP) decoding of nonbinary linear codes
over rings is developed. This framework facilitates linear-programming based
reception for coded modulation systems which use direct modulation mapping of
coded symbols. It is proved that the resulting LP decoder has the
'maximum-likelihood certificate' property. It is also shown that the decoder
output is the lowest cost pseudocodeword. Equivalence between pseudocodewords
of the linear program and pseudocodewords of graph covers is proved. It is also
proved that if the modulator-channel combination satisfies a particular
symmetry condition, the codeword error rate performance is independent of the
transmitted codeword. Two alternative polytopes for use with linear-programming
decoding are studied, and it is shown that for many classes of codes these
polytopes yield a complexity advantage for decoding. These polytope
representations lead to polynomial-time decoders for a wide variety of
classical nonbinary linear codes. LP decoding performance is illustrated for
the [11,6] ternary Golay code with ternary PSK modulation over AWGN, and in
this case it is shown that the performance of the LP decoder is comparable to
codeword-error-rate-optimum hard-decision based decoding. LP decoding is also
simulated for medium-length ternary and quaternary LDPC codes with
corresponding PSK modulations over AWGN.
|
0804.4391
|
A Lower Bound on the Bayesian MSE Based on the Optimal Bias Function
|
cs.IT math.IT
|
A lower bound on the minimum mean-squared error (MSE) in a Bayesian
estimation problem is proposed in this paper. This bound utilizes a well-known
connection to the deterministic estimation setting. Using the prior
distribution, the bias function which minimizes the Cramer-Rao bound can be
determined, resulting in a lower bound on the Bayesian MSE. The bound is
developed for the general case of a vector parameter with an arbitrary
probability distribution, and is shown to be asymptotically tight in both the
high and low signal-to-noise ratio regimes. A numerical study demonstrates
several cases in which the proposed technique is both simpler to compute and
tighter than alternative methods.
|
0804.4395
|
Development of a peristaltic micropump for bio-medical applications
based on mini LIPCA
|
cs.RO
|
This paper presents the design, fabrication, and experimental
characterization of a peristaltic micropump. The micropump is composed of two
layers fabricated from polydimethylsiloxane (PDMS) material. The first layer
has a rectangular channel and two valve seals. Three rectangular mini
lightweight piezo-composite actuators are integrated in the second layer, and
used as actuation parts. Two layers are bonded, and covered by two polymethyl
methacrylate (PMMA) plates, which help increase the stiffness of the micropump.
A maximum flow rate of 900 mokroliter per min and a maximum backpressure of 1.8
kPa are recorded when water is used as pump liquid. We measured the power
consumption of the micropump. The micropump is found to be a promising
candidate for bio-medical application due to its bio-compatibility,
portability, bidirectionality, and simple effective design.
|
0804.4451
|
Dependence Structure Estimation via Copula
|
cs.LG cs.IR stat.ME
|
Dependence strucuture estimation is one of the important problems in machine
learning domain and has many applications in different scientific areas. In
this paper, a theoretical framework for such estimation based on copula and
copula entropy -- the probabilistic theory of representation and measurement of
statistical dependence, is proposed. Graphical models are considered as a
special case of the copula framework. A method of the framework for estimating
maximum spanning copula is proposed. Due to copula, the method is irrelevant to
the properties of individual variables, insensitive to outlier and able to deal
with non-Gaussianity. Experiments on both simulated data and real dataset
demonstrated the effectiveness of the proposed method.
|
0804.4455
|
On the Capacity Bounds of Undirected Networks
|
cs.IT math.IT
|
In this work we improve on the bounds presented by Li&Li for network coding
gain in the undirected case. A tightened bound for the undirected multicast
problem with three terminals is derived. An interesting result shows that with
fractional routing, routing throughput can achieve at least 75% of the coding
throughput. A tighter bound for the general multicast problem with any number
of terminals shows that coding gain is strictly less than 2. Our derived bound
depends on the number of terminals in the multicast network and approaches 2
for arbitrarily large number of terminals.
|
0804.4466
|
Free Distance Bounds for Protograph-Based Regular LDPC Convolutional
Codes
|
cs.IT math.IT
|
In this paper asymptotic methods are used to form lower bounds on the free
distance to constraint length ratio of several ensembles of regular,
asymptotically good, protograph-based LDPC convolutional codes. In particular,
we show that the free distance to constraint length ratio of the regular LDPC
convolutional codes exceeds that of the minimum distance to block length ratio
of the corresponding LDPC block codes.
|
0804.4489
|
Generalized Degrees of Freedom of the Symmetric Gaussian $K$ User
Interference Channel
|
cs.IT math.IT
|
We characterize the generalized degrees of freedom of the $K$ user symmetric
Gaussian interference channel where all desired links have the same
signal-to-noise ratio (SNR) and all undesired links carrying interference have
the same interference-to-noise ratio, ${INR}={SNR}^\alpha$. We find that the
number of generalized degrees of freedom per user, $d(\alpha)$, does not depend
on the number of users, so that the characterization is identical to the 2 user
interference channel with the exception of a singularity at $\alpha=1$ where
$d(1)=\frac{1}{K}$. The achievable schemes use multilevel coding with a nested
lattice structure that opens the possibility that the sum of interfering
signals can be decoded at a receiver even though the messages carried by the
interfering signals are not decodable.
|
0804.4517
|
A multivariate generalization of Costa's entropy power inequality
|
cs.IT math.IT
|
A simple multivariate version of Costa's entropy power inequality is proved.
In particular, it is shown that if independent white Gaussian noise is added to
an arbitrary multivariate signal, the entropy power of the resulting random
variable is a multidimensional concave function of the individual variances of
the components of the signal. As a side result, we also give an expression for
the Hessian matrix of the entropy and entropy power functions with respect to
the variances of the signal components, which is an interesting result in its
own right.
|
0804.4584
|
Feature Unification in TAG Derivation Trees
|
cs.CL
|
The derivation trees of a tree adjoining grammar provide a first insight into
the sentence semantics, and are thus prime targets for generation systems. We
define a formalism, feature-based regular tree grammars, and a translation from
feature based tree adjoining grammars into this new formalism. The translation
preserves the derivation structures of the original grammar, and accounts for
feature unification.
|
0804.4622
|
Fast Density Codes for Image Data
|
cs.NE
|
Recently, a new method for encoding data sets in the form of "Density Codes"
was proposed in the literature (Courrieu, 2006). This method allows to compare
sets of points belonging to every multidimensional space, and to build shape
spaces invariant to a wide variety of affine and non-affine transformations.
However, this general method does not take advantage of the special properties
of image data, resulting in a quite slow encoding process that makes this tool
practically unusable for processing large image databases with conventional
computers. This paper proposes a very simple variant of the density code method
that directly works on the image function, which is thousands times faster than
the original Parzen window based method, without loss of its useful properties.
|
0804.4662
|
Rateless Coding for MIMO Block Fading Channels
|
cs.IT math.IT
|
In this paper the performance limits and design principles of rateless codes
over fading channels are studied. The diversity-multiplexing tradeoff (DMT) is
used to analyze the system performance for all possible transmission rates. It
is revealed from the analysis that the design of such rateless codes follows
the design principle of approximately universal codes for parallel
multiple-input multiple-output (MIMO) channels, in which each sub-channel is a
MIMO channel. More specifically, it is shown that for a single-input
single-output (SISO) channel, the previously developed permutation codes of
unit length for parallel channels having rate LR can be transformed directly
into rateless codes of length L having multiple rate levels (R, 2R, . . ., LR),
to achieve the DMT performance limit.
|
0804.4682
|
Introduction to Relational Networks for Classification
|
cs.LG
|
The use of computational intelligence techniques for classification has been
used in numerous applications. This paper compares the use of a Multi Layer
Perceptron Neural Network and a new Relational Network on classifying the HIV
status of women at ante-natal clinics. The paper discusses the architecture of
the relational network and its merits compared to a neural network and most
other computational intelligence classifiers. Results gathered from the study
indicate comparable classification accuracies as well as revealed relationships
between data features in the classification data. Much higher classification
accuracies are recommended for future research in the area of HIV
classification as well as missing data estimation.
|
0804.4701
|
Superposition-Coded Concurrent Decode-and-Forward Relaying
|
cs.IT math.IT
|
In this paper, a superposition-coded concurrent decode-and-forward (DF)
relaying protocol is presented. A specific scenario, where the inter-relay
channel is sufficiently strong, is considered. Assuming perfect source-relay
transmissions, the proposed scheme further improves the diversity performance
of previously proposed repetition-coded concurrent DF relaying, in which the
advantage of the inter-relay interference is not fully extracted.
|
0804.4714
|
Network Structure and Dynamics, and Emergence of Robustness by
Stabilizing Selection in an Artificial Genome
|
q-bio.MN cond-mat.dis-nn cs.NE q-bio.GN q-bio.PE
|
Genetic regulation is a key component in development, but a clear
understanding of the structure and dynamics of genetic networks is not yet at
hand. In this work we investigate these properties within an artificial genome
model originally introduced by Reil. We analyze statistical properties of
randomly generated genomes both on the sequence- and network level, and show
that this model correctly predicts the frequency of genes in genomes as found
in experimental data. Using an evolutionary algorithm based on stabilizing
selection for a phenotype, we show that robustness against single base
mutations, as well as against random changes in initial network states that
mimic stochastic fluctuations in environmental conditions, can emerge in
parallel. Evolved genomes exhibit characteristic patterns on both sequence and
network level.
|
0804.4717
|
Intelligent Unmanned Explorer for Deep Space Exploration
|
cs.RO
|
asteroids or comets have received remarkable attention in the world. In small
body explorations, especially, detailed in-situ surface exploration by tiny
rover is one of effective and fruitful means and is expected to make strong
contributions towards scientific studies. JAXA ISAS is promoting MUSES C
mission, which is the worlds first sample and return attempt to or from the
near earth asteroid. Hayabusa spacecraft in MUSES C mission took the tiny
rover, which was expected to perform the in-situ surface exploration by
hopping. This paper describes the system design, mobility and intelligence of
the developed unmanned explorer. This paper also presents the ground
experimental results and the flight results.
|
0804.4740
|
An Affine-invariant Time-dependent Triangulation of Spatio-temporal Data
|
cs.CG cs.DB
|
In the geometric data model for spatio-temporal data, introduced by Chomicki
and Revesz, spatio-temporal data are modelled as a finite collection of
triangles that are transformed by time-dependent affinities of the plane. To
facilitate querying and animation of spatio-temporal data, we present a normal
form for data in the geometric data model. We propose an algorithm for
constructing this normal form via a spatio-temporal triangulation of geometric
data objects. This triangulation algorithm generates new geometric data objects
that partition the given objects both in space and in time. A particular
property of the proposed partition is that it is invariant under time-dependent
affine transformations, and hence independent of the particular choice of
coordinate system used to describe he spatio-temporal data in. We can show that
our algorithm works correctly and has a polynomial time complexity (of
reasonably low degree in the number of input triangles and the maximal degree
of the polynomial functions that describe the transformation functions). We
also discuss several possible applications of this spatio-temporal
triangulation.
|
0804.4741
|
The Effect of Structural Diversity of an Ensemble of Classifiers on
Classification Accuracy
|
cs.LG
|
This paper aims to showcase the measure of structural diversity of an
ensemble of 9 classifiers and then map a relationship between this structural
diversity and accuracy. The structural diversity was induced by having
different architectures or structures of the classifiers The Genetical
Algorithms (GA) were used to derive the relationship between diversity and the
classification accuracy by evolving the classifiers and then picking 9
classifiers out on an ensemble of 60 classifiers. It was found that as the
ensemble became diverse the accuracy improved. However at a certain diversity
measure the accuracy began to drop. The Kohavi-Wolpert variance method is used
to measure the diversity of the ensemble. A method of voting is used to
aggregate the results from each classifier. The lowest error was observed at a
diversity measure of 0.16 with a mean square error of 0.274, when taking 0.2024
as maximum diversity measured. The parameters that were varied were: the number
of hidden nodes, learning rate and the activation function.
|
0804.4749
|
Study of improving nano-contouring performance by employing
cross-coupling controller
|
cs.RO
|
For the tracking stage path planning, we design a two-axis cross-coupling
control system which uses the PI controller to compensate the contour error
between axes. In this paper, the stage adoptive is designed by our laboratory
(Precision Machine Center of National Formosa University). The cross-coupling
controller calculates the actuating signal of each axis by combining multi-axes
position error. Hence, the cross-coupling controller improves the stage
tracking ability and decreases the contour error. The experiments show
excellent stage motion. This finding confirms that the proposed method is a
powerful and efficient tool for improving stage tracking ability. Also found
were the stages tracking to minimize contour error of two types circular to
approximately 25nm.
|
0804.4750
|
The Numerical Control Design for a Pair of Dubins Vehicles
|
cs.RO
|
In this paper, a model of a pair of Dubins vehicles is considered. The
vehicles move from an initial position and orientation to final position and
orientation. A long the motion, the two vehicles are not allowed to collide
however the two vehicles cant to far each other. The optimal control of the
vehicle is found using the Pontryagins Maximum Principle (PMP). This PMP leads
to a Hamiltonian system consisting of a system of differential equation and its
adjoint. The originally differential equation has initial and final condition
but the adjoint system doesn't have one. The classical difficulty is solved
numerically by the greatest gradient descent method. Some simulation results
are presented in this paper.
|
0804.4752
|
Simulation of Dynamic Yaw Stability Derivatives of a Bird Using CFD
|
cs.RO
|
Simulation results on dynamic yaw stability derivatives of a gull bird by
means of computational fluid dynamics are presented. Two different kinds of
motions are used for determining the dynamic yaw stability derivatives CNr and
CNbeta . Concerning the first one, simple lateral translation and yaw rotary
motions in yaw are considered. The second one consists of combined motions. To
determine dynamic yaw stability derivatives of the bird, the simulation of an
unsteady flow with a bird model showing a harmonic motion is performed. The
unsteady flow solution for each time step is obtained by solving unsteady Euler
equations based on a finite volume approach for a smaller reduced frequency.
Then, an evaluation of unsteady forces and moments for one cycle is conducted
using harmonic Fourier analysis. The results on the dynamic yaw stability
derivatives for both simulations of the model motion show a good agreement.
|
0804.4753
|
Wavelet Based Iterative Learning Control with Fuzzy PD Feedback for
Position Tracking of A Pneumatic Servo System
|
cs.RO
|
In this paper, a wavelet-based iterative learning control (WILC) scheme with
Fuzzy PD feedback is presented for a pneumatic control system with nonsmooth
nonlinearities and uncertain parameters. The wavelet transform is employed to
extract the learnable dynamics from measured output signal before it can be
used to update the control profile. The wavelet transform is adopted to
decompose the original signal into many low-resolution signals that contain the
learnable and unlearnable parts. The desired control profile is then compared
with the learnable part of the transformed signal. Thus, the effects from
unlearnable dynamics on the controlled system can be attenuated by a Fuzzy PD
feedback controller. As for the rules of Fuzzy PD controller in the feedback
loop, a genetic algorithm (GA) is employed to search for the inference rules of
optimization. A proportional-valve controlled pneumatic cylinder actuator
system is used as the control target for simulation. Simulation results have
shown a much-improved positiontracking performance.
|
0804.4754
|
Positive Real Synthesis of Networked Control System An LMI Approach
|
cs.RO
|
This paper presents the positive real analysis and synthesis for Networked
Control Systems (NCS) in discrete time. Based on the definition of passivity,
the sufficient condition of NCS is given by stochastic Lyapunov functional. The
controller via state feedback is designed to guarantee the stability of NCS and
closed-loop positive realness. It is shown that a mode-dependent positive real
controller exists if a set of coupled linear matrix inequalities has solutions.
The controller can be then constructed in terms of the solutions.
|
0804.4757
|
Analysis of Stability, Response and LQR Controller Design of a Small
Scale Helicopter Dynamics
|
cs.RO
|
This paper presents how to use feedback controller with helicopter dynamics
state space model. A simplified analysis is presented for controller design
using LQR of small scale helicopters for axial and forward flights. Our
approach is simple and gives the basic understanding about how to develop
controller for solving the stability of linear helicopter flight dynamics.
|
0804.4759
|
Design and control of dynamical quantum processes in ortho para H2
conversion on surfaces
|
cs.RO
|
We present here a novel, cost-effective method for increasing and controlling
the ortho para H2 (o p H2) conversion yield. First, we invoke two processes
derived from fundamental, surface science insights, based on the effect of
molecular orientation on the hydrogen solid surface reaction, i.e., dynamical
quantum filtering and steering, and apply them to enhance the o p H2 conversion
yield. Second, we find an important factor that can significantly influence the
yield i.e., inhomogeneity of spin density distribution. This factor gives us a
promising possibility to increase the yield and to find the best catalyst e.g.,
design of materials that can function as catalysts for the o p H2 conversion.
|
0804.4774
|
A Projection Method for Derivation of Non-Shannon-Type Information
Inequalities
|
cs.IT math.IT
|
In 1998, Zhang and Yeung found the first unconditional non-Shannon-type
information inequality. Recently, Dougherty, Freiling and Zeger gave six new
unconditional non-Shannon-type information inequalities. This work generalizes
their work and provides a method to systematically derive non-Shannon-type
information inequalities. An application of this method reveals new 4-variable
non-Shannon-type information inequalities.
|
0804.4799
|
A Few More Quadratic APN Functions
|
cs.IT math.IT
|
We present two infinite families of APN functions where the degree of the
field is divisible by 3 but not 9. Our families contain two already known
families as special cases. We also discuss the inequivalence proof (by
computation) which shows that these functions are new.
|
0804.4808
|
Solving Time of Least Square Systems in Sigma-Pi Unit Networks
|
cs.NE
|
The solving of least square systems is a useful operation in
neurocomputational modeling of learning, pattern matching, and pattern
recognition. In these last two cases, the solution must be obtained on-line,
thus the time required to solve a system in a plausible neural architecture is
critical. This paper presents a recurrent network of Sigma-Pi neurons, whose
solving time increases at most like the logarithm of the system size, and of
its condition number, which provides plausible computation times for biological
systems.
|
0804.4809
|
Fast Computation of Moore-Penrose Inverse Matrices
|
cs.NE
|
Many neural learning algorithms require to solve large least square systems
in order to obtain synaptic weights. Moore-Penrose inverse matrices allow for
solving such systems, even with rank deficiency, and they provide minimum-norm
vectors of synaptic weights, which contribute to the regularization of the
input-output mapping. It is thus of interest to develop fast and accurate
algorithms for computing Moore-Penrose inverse matrices. In this paper, an
algorithm based on a full rank Cholesky factorization is proposed. The
resulting pseudoinverse matrices are similar to those provided by other
algorithms. However the computation time is substantially shorter, particularly
for large systems.
|
0804.4866
|
Sum-Capacity of Ergodic Fading Interference and Compound Multiaccess
Channels
|
cs.IT math.IT
|
The problem of resource allocation is studied for two-sender two-receiver
fading Gaussian interference channels (IFCs) and compound multiaccess channels
(C-MACs). The senders in an IFC communicate with their own receiver (unicast)
while those in a C-MAC communicate with both receivers (multicast). The
instantaneous fading state between every transmit-receive pair in this network
is assumed to be known at all transmitters and receivers. Under an average
power constraint at each source, the sum-capacity of the C-MAC and the power
policy that achieves this capacity is developed. The conditions defining the
classes of strong and very strong ergodic IFCs are presented and the multicast
sum-capacity is shown to be tight for both classes.
|
0804.4885
|
SimDialog: A visual game dialog editor
|
cs.HC cs.AI
|
SimDialog is a visual editor for dialog in computer games. This paper
presents the design of SimDialog, illustrating how script writers and
non-programmers can easily create dialog for video games with complex branching
structures and dynamic response characteristics. The system creates dialog as a
directed graph. This allows for play using the dialog with a state-based cause
and effect system that controls selection of non-player character responses and
can provide a basic scoring mechanism for games.
|
0804.4898
|
A Quadratic Loss Multi-Class SVM
|
cs.LG
|
Using a support vector machine requires to set two types of hyperparameters:
the soft margin parameter C and the parameters of the kernel. To perform this
model selection task, the method of choice is cross-validation. Its
leave-one-out variant is known to produce an estimator of the generalization
error which is almost unbiased. Its major drawback rests in its time
requirement. To overcome this difficulty, several upper bounds on the
leave-one-out error of the pattern recognition SVM have been derived. Among
those bounds, the most popular one is probably the radius-margin bound. It
applies to the hard margin pattern recognition SVM, and by extension to the
2-norm SVM. In this report, we introduce a quadratic loss M-SVM, the M-SVM^2,
as a direct extension of the 2-norm SVM to the multi-class case. For this
machine, a generalized radius-margin bound is then established.
|
0805.0012
|
Joint Physical Layer Coding and Network Coding for Bi-Directional
Relaying
|
cs.IT math.IT
|
We consider the problem of two transmitters wishing to exchange information
through a relay in the middle. The channels between the transmitters and the
relay are assumed to be synchronized, average power constrained additive white
Gaussian noise channels with a real input with signal-to-noise ratio (SNR) of
snr. An upper bound on the capacity is 1/2 log(1+ snr) bits per transmitter per
use of the medium-access phase and broadcast phase of the bi-directional relay
channel. We show that using lattice codes and lattice decoding, we can obtain a
rate of 1/2 log(0.5 + snr) bits per transmitter, which is essentially optimal
at high SNRs. The main idea is to decode the sum of the codewords modulo a
lattice at the relay followed by a broadcast phase which performs Slepian-Wolf
coding with structured codes. For asymptotically low SNR's, jointly decoding
the two transmissions at the relay (MAC channel) is shown to be optimal. We
also show that if the two transmitters use identical lattices with minimum
angle decoding, we can achieve the same rate of 1/2 log(0.5 + snr). The
proposed scheme can be thought of as a joint physical layer, network layer code
which outperforms other recently proposed analog network coding schemes.
|
0805.0034
|
Diversity Order Gain with Noisy Feedback in Multiple Access Channels
|
cs.IT math.IT
|
In this paper, we study the effect of feedback channel noise on the
diversity-multiplexing tradeoff in multiuser MIMO systems using quantized
feedback, where each user has m transmit antennas and the base-station receiver
has n antennas. We derive an achievable tradeoff and use it to show that in
SNR-symmetric channels, a single bit of imperfect feedback is sufficient to
double the maximum diversity order to 2mn compared to when there is no feedback
(maximum is mn at multiplexing gain of zero). Further, additional feedback bits
do not increase this maximum diversity order beyond 2mn. Finally, the above
diversity order gain of mn over non-feedback systems can also be achieved for
higher multiplexing gains, albeit requiring more than one bit of feedback.
|
0805.0050
|
On the k-pairs problem
|
cs.IT math.IT
|
We consider network coding rates for directed and undirected $k$-pairs
networks. For directed networks, meagerness is known to be an upper bound on
network coding rates. We show that network coding rate can be $\Theta(|V|)$
multiplicative factor smaller than meagerness. For the undirected case, we show
some progress in the direction of the $k$-pairs conjecture.
|
0805.0051
|
Communicating the sum of sources over a network
|
cs.IT math.IT
|
We consider a network (that is capable of network coding) with a set of
sources and terminals, where each terminal is interested in recovering the sum
of the sources. Considering directed acyclic graphs with unit capacity edges
and independent, unit-entropy sources, we show the rate region when (a) there
are two sources and $n$ terminals, and (b) $n$ sources and two terminals. In
these cases as long as there exists at least one path from each source to each
terminal we demonstrate that there exists a valid assignment of coding vectors
to the edges such that the terminals can recover the sum of the sources.
|
0805.0053
|
Particle Filtering for Large Dimensional State Spaces with Multimodal
Observation Likelihoods
|
cs.IT math.IT math.ST stat.ME stat.TH
|
We study efficient importance sampling techniques for particle filtering (PF)
when either (a) the observation likelihood (OL) is frequently multimodal or
heavy-tailed, or (b) the state space dimension is large or both. When the OL is
multimodal, but the state transition pdf (STP) is narrow enough, the optimal
importance density is usually unimodal. Under this assumption, many techniques
have been proposed. But when the STP is broad, this assumption does not hold.
We study how existing techniques can be generalized to situations where the
optimal importance density is multimodal, but is unimodal conditioned on a part
of the state vector. Sufficient conditions to test for the unimodality of this
conditional posterior are derived. The number of particles, N, to accurately
track using a PF increases with state space dimension, thus making any regular
PF impractical for large dimensional tracking problems. We propose a solution
that partially addresses this problem. An important class of large dimensional
problems with multimodal OL is tracking spatially varying physical quantities
such as temperature or pressure in a large area using a network of sensors
which may be nonlinear and/or may have non-negligible failure probabilities.
|
0805.0065
|
Communication Requirements for Generating Correlated Random Variables
|
cs.IT cs.GT math.IT math.PR
|
Two familiar notions of correlation are rediscovered as extreme operating
points for simulating a discrete memoryless channel, in which a channel output
is generated based only on a description of the channel input. Wyner's "common
information" coincides with the minimum description rate needed. However, when
common randomness independent of the input is available, the necessary
description rate reduces to Shannon's mutual information. This work
characterizes the optimal tradeoff between the amount of common randomness used
and the required rate of description.
|
0805.0092
|
Cellular Systems with Full-Duplex Compress-and-Forward Relaying and
Cooperative Base Stations
|
cs.IT math.IT
|
In this paper the advantages provided by multicell processing of signals
transmitted by mobile terminals (MTs) which are received via dedicated relay
terminals (RTs) are studied. It is assumed that each RT is capable of
full-duplex operation and receives the transmission of adjacent relay
terminals. Focusing on intra-cell TDMA and non-fading channels, a simplified
relay-aided uplink cellular model based on a model introduced by Wyner is
considered. Assuming a nomadic application in which the RTs are oblivious to
the MTs' codebooks, a form of distributed compress-and-forward (CF) scheme with
decoder side information is employed. The per-cell sum-rate of the CF scheme is
derived and is given as a solution of a simple fixed point equation. This
achievable rate reveals that the CF scheme is able to completely eliminate the
inter-relay interference, and it approaches a ``cut-set-like'' upper bound for
strong RTs transmission power. The CF rate is also shown to surpass the rate of
an amplify-and-forward scheme via numerical calculations for a wide range of
the system parameters.
|
0805.0108
|
The Gaussian Wiretap Channel with a Helping Interferer
|
cs.IT cs.CR math.IT
|
Due to the broadcast nature of the wireless medium, wireless communication is
susceptible to adversarial eavesdropping. This paper describes how
eavesdropping can potentially be defeated by exploiting the superposition
nature of the wireless medium. A Gaussian wire-tap channel with a helping
interferer (WTC-HI) is considered in which a transmitter sends confidential
messages to its intended receiver in the presence of a passive eavesdropper and
with the help of an interferer. The interferer, which does not know the
confidential message assists the confidential message transmission by sending a
signal that is independent of the transmitted message. An achievable secrecy
rate and a Sato-type upper bound on the secrecy capacity are given for the
Gaussian WTC-HI. Through numerical analysis, it is found that the upper bound
is close to the achievable secrecy rate when the interference is weak for
symmetric interference channels, and under more general conditions for
asymmetric Gaussian interference channels.
|
0805.0120
|
Nonnegative Matrix Factorization via Rank-One Downdate
|
cs.IR cs.NA
|
Nonnegative matrix factorization (NMF) was popularized as a tool for data
mining by Lee and Seung in 1999. NMF attempts to approximate a matrix with
nonnegative entries by a product of two low-rank matrices, also with
nonnegative entries. We propose an algorithm called rank-one downdate (R1D) for
computing a NMF that is partly motivated by singular value decomposition. This
algorithm computes the dominant singular values and vectors of adaptively
determined submatrices of a matrix. On each iteration, R1D extracts a rank-one
submatrix from the dataset according to an objective function. We establish a
theoretical result that maximizing this objective function corresponds to
correctly classifying articles in a nearly separable corpus. We also provide
computational experiments showing the success of this method in identifying
features in realistic datasets.
|
0805.0129
|
On some entropy functionals derived from R\'enyi information divergence
|
cs.IT cond-mat.other math.IT
|
We consider the maximum entropy problems associated with R\'enyi $Q$-entropy,
subject to two kinds of constraints on expected values. The constraints
considered are a constraint on the standard expectation, and a constraint on
the generalized expectation as encountered in nonextensive statistics. The
optimum maximum entropy probability distributions, which can exhibit a
power-law behaviour, are derived and characterized. The R\'enyi entropy of the
optimum distributions can be viewed as a function of the constraint. This
defines two families of entropy functionals in the space of possible expected
values. General properties of these functionals, including nonnegativity,
minimum, convexity, are documented. Their relationships as well as numerical
aspects are also discussed. Finally, we work out some specific cases for the
reference measure $Q(x)$ and recover in a limit case some well-known entropies.
|
0805.0131
|
Diversity-Multiplexing Tradeoff in Selective-Fading Multiple-Access MIMO
Channels
|
cs.IT math.IT
|
We establish the optimal diversity-multiplexing (DM) tradeoff of coherent
selective-fading multiple-access multiple-input multiple-output (MIMO) channels
and provide corresponding code design criteria. As a byproduct, on the
conceptual level, we find an interesting relation between the DM tradeoff
framework and the notion of dominant error event regions which was first
introduced in the AWGN case by Gallager, IEEE Trans. IT, 1985. This relation
allows to accurately characterize the error mechanisms in MIMO fading
multiple-access channels. In particular, we find that, for a given rate tuple,
the maximum achievable diversity order is determined by the error event that
dominates the total error probability exponentially in SNR. Finally, we show
that the distributed space-time code construction proposed recently by Badr and
Belfiore, Int. Zurich Seminar on Commun., 2008, satisfies the code design
criteria derived in this paper.
|
0805.0149
|
On Recovery of Sparse Signals via $\ell_1$ Minimization
|
cs.LG
|
This article considers constrained $\ell_1$ minimization methods for the
recovery of high dimensional sparse signals in three settings: noiseless,
bounded error and Gaussian noise. A unified and elementary treatment is given
in these noise settings for two $\ell_1$ minimization methods: the Dantzig
selector and $\ell_1$ minimization with an $\ell_2$ constraint. The results of
this paper improve the existing results in the literature by weakening the
conditions and tightening the error bounds. The improvement on the conditions
shows that signals with larger support can be recovered accurately. This paper
also establishes connections between restricted isometry property and the
mutual incoherence property. Some results of Candes, Romberg and Tao (2006) and
Donoho, Elad, and Temlyakov (2006) are extended.
|
0805.0154
|
The Tsallis entropy and the Shannon entropy of a universal probability
|
cs.IT cs.CC math.IT
|
We study the properties of Tsallis entropy and Shannon entropy from the point
of view of algorithmic randomness. In algorithmic information theory, there are
two equivalent ways to define the program-size complexity K(s) of a given
finite binary string s. In the standard way, K(s) is defined as the length of
the shortest input string for the universal self-delimiting Turing machine to
output s. In the other way, the so-called universal probability m is introduced
first, and then K(s) is defined as -log_2 m(s) without reference to the concept
of program-size. In this paper, we investigate the properties of the Shannon
entropy, the power sum, and the Tsallis entropy of a universal probability by
means of the notion of program-size complexity. We determine the convergence or
divergence of each of these three quantities, and evaluate its degree of
randomness if it converges.
|
0805.0173
|
A Computer Search for N1L-Configurations
|
cs.IT math.IT
|
In an earlier paper the author defined N1L configurations, and stated a
conjecture concerning them which would lead to an improvement by a constant
factor to the sphere-packing bound for linear double error correcting codes.
Here a computer search is presented, in an effort to gather evidence on the
conjecture.
|
0805.0184
|
Information, Energy and Density for Ad Hoc Sensor Networks over
Correlated Random Fields: Large Deviations Analysis
|
cs.IT math.IT
|
Using large deviations results that characterize the amount of information
per node on a two-dimensional (2-D) lattice, asymptotic behavior of a sensor
network deployed over a correlated random field for statistical inference is
investigated. Under a 2-D hidden Gauss-Markov random field model with symmetric
first order conditional autoregression, the behavior of the total information
[nats] and energy efficiency [nats/J] defined as the ratio of total gathered
information to the required energy is obtained as the coverage area, node
density and energy vary.
|
0805.0192
|
Specification of an extensible and portable file format for electronic
structure and crystallographic data
|
cs.DL cond-mat.mtrl-sci cs.DB
|
In order to allow different software applications, in constant evolution, to
interact and exchange data, flexible file formats are needed. A file format
specification for different types of content has been elaborated to allow
communication of data for the software developed within the European Network of
Excellence "NANOQUANTA", focusing on first-principles calculations of materials
and nanosystems. It might be used by other software as well, and is described
here in detail. The format relies on the NetCDF binary input/output library,
already used in many different scientific communities, that provides
flexibility as well as portability accross languages and platforms. Thanks to
NetCDF, the content can be accessed by keywords, ensuring the file format is
extensible and backward compatible.
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.