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We study selective monitors for labelled Markov chains. Monitors observe the outputs that are generated by a Markov chain during its run, with the goal of identifying runs as correct or faulty. A monitor is selective if it skips…

Formal Languages and Automata Theory · Computer Science 2018-07-03 Radu Grigore , Stefan Kiefer

Using a mild variant of polar codes we design linear compression schemes compressing Hidden Markov sources (where the source is a Markov chain, but whose state is not necessarily observable from its output), and to decode from Hidden Markov…

Information Theory · Computer Science 2018-10-05 Venkatesan Guruswami , Preetum Nakkiran , Madhu Sudan

The problem of computing a linear combination of sources over a multiple access channel is studied. Inner and outer bounds on the optimal tradeoff between the communication rates are established when encoding is restricted to random…

Information Theory · Computer Science 2018-10-30 Pinar Sen , Sung Hoon Lim , Young-Han Kim

This paper introduces an objective function that seeks to minimise the average total number of bits required to encode the joint state of all of the layers of a Markov source. This type of encoder may be applied to the problem of optimising…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Stephen Luttrell

The process of dynamic state estimation (filtering) based on point process observations is in general intractable. Numerical sampling techniques are often practically useful, but lead to limited conceptual insight about optimal…

Machine Learning · Statistics 2015-08-04 Yuval Harel , Ron Meir , Manfred Opper

We present an alternative view for the study of optimal control of partially observed Markov Decision Processes (POMDPs). We first revisit the traditional (and by now standard) separated-design method of reducing the problem to fully…

Optimization and Control · Mathematics 2024-12-20 Serdar Yüksel

This paper characterizes the second-order coding rates for lossy source coding with side information available at both the encoder and the decoder. We first provide non-asymptotic bounds for this problem and then specialize the…

Information Theory · Computer Science 2014-10-13 Sy-Quoc Le , Vincent Y. F. Tan , Mehul Motani

We consider zero-delay single-user and multi-user source coding with average distortion constraint and decoder side information. The zero-delay constraint translates into causal (sequential) encoder and decoder pairs as well as the use of…

Information Theory · Computer Science 2013-01-03 Yonatan Kaspi , Neri Merhav

The notion of a successful coupling of Markov processes, based on the idea that both components of the coupled system ``intersect'' in finite time with probability one, is extended to cover situations when the coupling is unnecessarily…

Probability · Mathematics 2007-05-23 Michael Blank , Sergey Pirogov

In this monograph, we review recent advances in second-order asymptotics for lossy source coding, which provides approximations to the finite blocklength performance of optimal codes. The monograph is divided into three parts. In part I, we…

Information Theory · Computer Science 2024-10-25 Lin Zhou , Mehul Motani

Computational level explanations based on optimal feedback control with signal-dependent noise have been able to account for a vast array of phenomena in human sensorimotor behavior. However, commonly a cost function needs to be assumed for…

Machine Learning · Computer Science 2021-10-22 Matthias Schultheis , Dominik Straub , Constantin A. Rothkopf

Motivated by the Internet-of-things and sensor networks for cyberphysical systems, the problem of dynamic sensor activation for the tracking of a time-varying process is examined. The tradeoff is between energy efficiency, which decreases…

Systems and Control · Computer Science 2017-11-30 Arpan Chattopadhyay , Urbashi Mitra

We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements from an underlying random process, code and transmit those…

Information Theory · Computer Science 2007-07-13 Nan Liu , Sennur Ulukus

We study the zero-error source coding problem in which an encoder with Side Information (SI) $g(Y)$ transmits source symbols $X$ to a decoder. The decoder has SI $Y$ and wants to recover $f(X,Y)$ where $f,g$ are deterministic. We exhibit a…

Information Theory · Computer Science 2022-12-19 Nicolas Charpenay , Maël le Treust , Aline Roumy

We study the problem of deinterleaving a set of finite-memory (Markov) processes over disjoint finite alphabets, which have been randomly interleaved by a finite-memory switch. The deinterleaver has access to a sample of the resulting…

Information Theory · Computer Science 2011-08-29 Gadiel Seroussi , Wojciech Szpankowski , Marcelo J. Weinberger

Transmission of a Gaussian source over a time-varying Gaussian channel is studied in the presence of time-varying correlated side information at the receiver. A block fading model is considered for both the channel and the side information,…

Information Theory · Computer Science 2015-05-27 Iñaki Estella Aguerri , Deniz Gündüz

This paper establishes the rate region for a class of source coding function computation setups where sources of information are available at the nodes of a tree and where a function of these sources must be computed at the root. The rate…

Information Theory · Computer Science 2015-04-08 Milad Sefidgaran , Aslan Tchamkerten

We study the classical problem of recovering a multidimensional source signal from observations of nonlinear mixtures of this signal. We show that this recovery is possible (up to a permutation and monotone scaling of the source's original…

Machine Learning · Statistics 2023-01-18 Alexander Schell , Harald Oberhauser

This paper proposes a practical successive decoding scheme with finite levels for the finite-state Markov channels where there is no a priori state information at the transmitter or the receiver. The design employs either a random…

Information Theory · Computer Science 2009-05-06 Teng Li , Oliver M. Collins

We derive novel upper and lower finite-length bounds of the error probability in joint source-channel coding when the source obeys an ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive…

Information Theory · Computer Science 2017-05-03 Ryo Yaguchi , Masahito Hayashi
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