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We consider the problem of lossy source coding with a mismatched distortion measure. That is, we investigate what distortion guarantees can be made with respect to distortion measure $\tilde{\rho}$, for a source code designed such that it…

Information Theory · Computer Science 2008-04-07 Urs Niesen , Devavrat Shah , Gregory Wornell

The "water-filling" solution for the quadratic rate-distortion function of a stationary Gaussian source is given in terms of its power spectrum. This formula naturally lends itself to a frequency domain "test-channel" realization. We…

Information Theory · Computer Science 2008-02-18 Ram Zamir , Yuval Kochman , Uri Erez

We investigate which loss functions provide better separations via benchmarking an extensive set of those for music source separation. To that end, we first survey the most representative audio source separation losses we identified, to…

Sound · Computer Science 2022-02-17 Enric Gusó , Jordi Pons , Santiago Pascual , Joan Serrà

For a number of lossy source coding problems it is shown that even if the usual single-letter sum-rate-distortion expressions may become invalid for non-infinite distortion functions, they can be approached, to any desired accuracy, via the…

Information Theory · Computer Science 2014-08-05 Prakash Ishwar

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

Since Shannon's foundational work, rate-distortion theory has defined the fundamental limits of lossy compression. Classical results, derived for memoryless and stationary ergodic sources in the asymptotic regime, have shaped both transform…

Information Theory · Computer Science 2026-03-11 Sujata Sinha , Vishwas Rao , Robert Underwood , David Lenz , Sheng Di , Franck Cappello , Lingjia Liu

This paper studies a variant of the rate-distortion problem motivated by task-oriented semantic communication and distributed learning problems, where $M$ correlated sources are independently encoded for a central decoder. The decoder has…

Information Theory · Computer Science 2024-05-24 Jiancheng Tang , Qianqian Yang , Deniz Gündüz

Around the mean dimensions and rate-distortion functions, using some tools from local entropy theory this paper establishes the following main results: $(1)$ We prove that for non-ergodic measures associated with almost sure processes, the…

Dynamical Systems · Mathematics 2025-10-10 Rui Yang

We approach index coding as a special case of rate-distortion with multiple receivers, each with some side information about the source. Specifically, using techniques developed for the rate-distortion problem, we provide two upper bounds…

Information Theory · Computer Science 2015-07-28 Sinem Unal , Aaron B. Wagner

In this paper we consider the rate distortion problem of discrete-time, ergodic, and stationary sources with feed forward at the receiver. We derive a sequence of achievable and computable rates that converge to the feed-forward rate…

Information Theory · Computer Science 2011-06-07 Iddo Naiss , Haim Permuter

The error exponent of fixed-length lossy source coding was established by Marton. Ahlswede showed that this exponent can be discontinuous at a rate $R$, depending on the probability distribution $P$ of the given information source and the…

Information Theory · Computer Science 2023-04-25 Yutaka Jitsumatsu

We begin by presenting a simple lossy compressor operating at near-zero rate: The encoder merely describes the indices of the few maximal source components, while the decoder's reconstruction is a natural estimate of the source components…

Information Theory · Computer Science 2016-03-09 Albert No , Tsachy Weissman

A receiver wants to compute a function of two correlated sources separately observed by two transmitters. One of the transmitters may send a possibly private message to the other transmitter in a cooperation phase before both transmitters…

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

This paper studies a variant of the rate-distortion problem motivated by task-oriented semantic communication and distributed learning systems, where $M$ correlated sources are independently encoded for a central decoder. The decoder has…

Information Theory · Computer Science 2025-01-24 Jiancheng Tang , Qianqian Yang

In this paper, we introduce new lower bounds on the distortion of scalar fixed-rate codes for lossy compression with side information available at the receiver. These bounds are derived by presenting the relevant random variables as a…

Information Theory · Computer Science 2014-11-18 Avraham Reani , Neri Merhav

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

We show the existence of variable-rate rate-distortion codes that meet the disortion constraint almost surely and are minimax, i.e., strongly, universal with respect to an unknown source distribution and a distortion measure that is…

Information Theory · Computer Science 2022-11-29 Adeel Mahmood , Aaron B. Wagner

Marton's optimal error exponent for the lossy source coding problem is defined as a non-convex optimization problem. This fact had prevented us to develop an efficient algorithm to compute it. This problem is caused by the fact that the…

Information Theory · Computer Science 2024-09-13 Yutaka Jitsumatsu

We study how the Shannon entropy of sequences produced by an information source converges to the source's entropy rate. We synthesize several phenomenological approaches to applying information theoretic measures of randomness and memory to…

Statistical Mechanics · Physics 2007-05-23 James P. Crutchfield , David P. Feldman

Rate distortion dimension describes the theoretical limit of lossy data compression methods as the distortion bound goes to zero. It was originally introduced in the context of information theory, and recently it was discovered that it has…

Dynamical Systems · Mathematics 2025-03-11 Masaki Tsukamoto
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