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This paper considers the joint compression of a pair of correlated sources, where the encoder is allowed to access only one of the sources. The objective is to recover both sources under separate distortion constraints for each source while…

Information Theory · Computer Science 2024-11-07 Huiyuan Yang , Yuxuan Shi , Shuo Shao , Xiaojun Yuan

We propose a framework for second-order achievability, called type deviation convergence, that is generally applicable to settings in network information theory, and is especially suitable for lossy source coding and channel coding with…

Information Theory · Computer Science 2025-10-24 Xiang Li , Cheuk Ting Li

The second-order achievable asymptotics in typical random number generation problems such as resolvability, intrinsic randomness, fixed-length source coding are considered. In these problems, several researchers have derived the first-order…

Information Theory · Computer Science 2013-01-01 Ryo Nomura , Te Sun Han

The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An explicit expression is obtained when both source and…

Information Theory · Computer Science 2024-03-25 Li Xie , Liangyan Li , Jun Chen , Zhongshan Zhang

The problem of side-information scalable (SI-scalable) source coding is considered in this work, where the encoder constructs a progressive description, such that the receiver with high quality side information will be able to truncate the…

Information Theory · Computer Science 2007-08-01 Chao Tian , Suhas N. Diggavi

We investigate the second order asymptotics (source dispersion) of the successive refinement problem. Similarly to the classical definition of a successively refinable source, we say that a source is strongly successively refinable if…

Information Theory · Computer Science 2016-03-16 Albert No , Amir Ingber , Tsachy Weissman

This paper studies the joint data and semantics lossy compression problem, i.e., an extension of the hidden lossy source coding problem that entails recovering both the hidden and observable sources. We aim to study the nonasymptotic and…

Information Theory · Computer Science 2024-08-20 Huiyuan Yang , Yuxuan Shi , Shuo Shao , Xiaojun Yuan

In this paper we study the nonasymptotic bounds of a special Joint Source-Channel Coding system with hierarchical source, where an observable source and an unobservable indirect source are required to be reconstructed. Namely, we focus on…

Information Theory · Computer Science 2026-03-17 Shuo Shao , Chao Qi , Jincheng Dai

In the Wyner-Ziv source coding problem, a source $X$ has to be encoded while the decoder has access to side information $Y$. This paper investigates the indirect setup, in which a latent source $S$, unobserved by both the encoder and the…

Information Theory · Computer Science 2025-07-25 Jiahui Wei , Philippe Mary , Elsa Dupraz

We study the mismatched successive refinement problem where one uses Gaussian codebooks to compress an arbitrary memoryless source with successive minimum Euclidean distance encoding under the quadratic distortion measure. Specifically, we…

Information Theory · Computer Science 2023-02-10 Lin Bai , Zhuangfei Wu , Lin Zhou

Recently, a secrecy measure based on list-reconstruction has been proposed [2], in which a wiretapper is allowed to produce a list of $2^{mR_{L}}$ reconstruction sequences and the secrecy is measured by the minimum distortion over the…

Information Theory · Computer Science 2017-07-25 Lei Yu , Houqiang Li , Weiping Li

We consider the lossy quantum source coding problem where the task is to compress a given quantum source below its von Neumann entropy. Inspired by the duality connections between the rate-distortion and channel coding problems in the…

Quantum Physics · Physics 2023-02-02 Touheed Anwar Atif , Mohammad Aamir Sohail , S. Sandeep Pradhan

We derive the optimal second-order coding region and moderate deviations constant for successive refinement source coding with a joint excess-distortion probability constraint. We consider two scenarios: (i) a discrete memoryless source…

Information Theory · Computer Science 2016-08-29 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

In the classical source coding problem, the compressed source is reconstructed at the decoder with respect to some distortion metric. Motivated by settings in which we are interested in more than simply reconstructing the compressed source,…

Information Theory · Computer Science 2023-10-03 Oğuzhan Kubilay Ülger , Elza Erkip

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

This paper investigates the problem of variable-length lossy source coding allowing a positive excess distortion probability and an overflow probability of codeword lengths. Novel one-shot achievability and converse bounds of the optimal…

Information Theory · Computer Science 2018-12-17 Shota Saito , Hideki Yagi , Toshiyasu Matsushima

In this paper, we revisit the discrete lossy Gray-Wyner problem. In particular, we derive its optimal second-order coding rate region, its error exponent (reliability function) and its moderate deviations constant under mild conditions on…

Information Theory · Computer Science 2017-01-05 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

This paper considers lossy source coding of $n$-dimensional memoryless sources and shows an explicit approximation to the minimum source coding rate required to sustain the probability of exceeding distortion $d$ no greater than $\epsilon$,…

Information Theory · Computer Science 2017-02-28 Victoria Kostina

The source-coding problem with side information at the decoder is studied subject to a constraint that the encoder---to whom the side information is unavailable---be able to compute the decoder's reconstruction sequence to within some…

Information Theory · Computer Science 2016-11-15 Amos Lapidoth , Andreas Malär , Michèle Wigger

In this work, lossy distributed compression of pairs of correlated sources is considered. Conventionally, Shannon's random coding arguments -- using randomly generated unstructured codebooks whose blocklength is taken to be asymptotically…

Information Theory · Computer Science 2020-10-21 Farhad Shirani , S. Sandeep Pradhan
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