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It is well known that independent (separate) encoding of K correlated sources may incur some rate loss compared to joint encoding, even if the decoding is done jointly. This loss is particularly evident in the multiple descriptions problem,…

Information Theory · Computer Science 2022-05-23 Jan Østergaard , Uri Erez , Ram Zamir

The problem of reconstructing a source sequence with the presence of decoder side-information that is mis-synchronized to the source due to deletions is studied in a distributed source coding framework. Motivated by practical applications,…

Information Theory · Computer Science 2016-11-17 Nan Ma , Kannan Ramchandran , David Tse

We study the problem of efficient compression of a stochastic source of probability distributions. It can be viewed as a generalization of Shannon's source coding problem. It has relation to the theory of common randomness, as well as to…

Quantum Physics · Physics 2016-09-08 Andreas Winter

A likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on the soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the soft-covering…

Information Theory · Computer Science 2016-04-07 Eva C. Song , Paul Cuff , H. Vincent Poor

We provide a complete characterization of the rate-distortion region for the multistage successive refinement of the Wyner-Ziv source coding problem with degraded side informations at the decoder. Necessary and sufficient conditions for a…

Information Theory · Computer Science 2007-07-13 Chao Tian , Suhas Diggavi

This paper studies a Shannon-theoretic version of the generalized distribution preserving quantization problem where a stationary and memoryless source is encoded subject to a distortion constraint and the additional requirement that the…

Information Theory · Computer Science 2015-07-10 Naci Saldi , Tamás Linder , Serdar Yüksel

Achievability and converse results for the lossy transmission of correlated sources over Shannon's two-way channels (TWCs) are presented. A joint source-channel coding theorem for independent sources and TWCs for which adaptation cannot…

Information Theory · Computer Science 2018-05-08 Jian-Jia Weng , Fady Alajaji , Tamás Linder

We propose two extensions to existing importance sampling based methods for lossy compression. First, we introduce an importance sampling based compression scheme that is a variant of ordered random coding (Theis and Ahmed, 2022) and is…

Information Theory · Computer Science 2024-03-11 Buu Phan , Ashish Khisti , Christos Louizos

In this paper, we study the asymptotic performance of Abelian group codes for the lossy source coding problem for arbitrary discrete (finite alphabet) memoryless sources as well as the channel coding problem for arbitrary discrete (finite…

Information Theory · Computer Science 2013-05-08 Aria G. Sahebi , S. Sandeep Pradhan

We consider the classical two-encoder multiterminal source coding problem where distortion is measured under logarithmic loss. We provide a single-letter characterization of the achievable rate distortion region for arbitrarily correlated…

Information Theory · Computer Science 2012-07-12 Thomas Courtade , Tsachy Weissman

The broadcast phase (downlink transmission) of the two-way relay network is studied in the source coding and joint source-channel coding settings. The rates needed for reliable communication are characterised for a number of special cases…

Information Theory · Computer Science 2010-11-23 Roy Timo , Alex Grant , Gerhard Kramer

We consider a joint source channel coding (JSCC) problem in which we desire to transmit an arbitrary memoryless source over an arbitrary additive channel. We propose a mismatched coding architecture that consists of Gaussian codebooks for…

Information Theory · Computer Science 2018-09-03 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

We show how real-number codes can be used to compress correlated sources, and establish a new framework for lossy distributed source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in…

Information Theory · Computer Science 2012-06-20 Mojtaba Vaezi , Fabrice Labeau

This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-channel code rate, and demonstrates that joint source-channel code design brings considerable performance advantage over a separate one in the…

Information Theory · Computer Science 2014-02-05 Victoria Kostina , Sergio Verdú

Distributed source coding is traditionally viewed in the block coding context -- all the source symbols are known in advance at the encoders. This paper instead considers a streaming setting in which iid source symbol pairs are revealed to…

Information Theory · Computer Science 2007-07-13 Cheng Chang , Stark Draper , Anant Sahai

We study finite-length bounds for source coding with side information for Markov sources and channel coding for channels with conditional Markovian additive noise. For this purpose, we propose two criteria for finite-length bounds. One is…

Information Theory · Computer Science 2017-01-10 Masahito Hayashi , Shun Watanabe

Motivated by the question of whether the recently introduced Reduced Cutset Coding (RCC) offers rate-complexity performance benefits over conventional context-based conditional coding for sources with two-dimensional Markov structure, this…

Information Theory · Computer Science 2017-02-28 Matthew G. Reyes , David L. Neuhoff

We study source coding in the presence of side information, when the system can take actions that affect the availability, quality, or nature of the side information. We begin by extending the Wyner-Ziv problem of source coding with decoder…

Information Theory · Computer Science 2009-04-30 Tsachy Weissman , Haim H. Permuter

A computable expression for the rate-distortion (RD) function proposed by Heegard and Berger has eluded information theory for nearly three decades. Heegard and Berger's single-letter achievability bound is well known to be optimal for…

Information Theory · Computer Science 2012-12-12 Roy Timo , Tobias J. Oechtering , Michèle Wigger

Stochastic encoders for channel coding and lossy source coding are introduced with a rate close to the fundamental limits, where the only restriction is that the channel input alphabet and the reproduction alphabet of the lossy source code…

Information Theory · Computer Science 2016-11-15 Jun Muramatsu
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