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In this work we investigate the behavior of the minimal rate needed in order to guarantee a given probability that the distortion exceeds a prescribed threshold, at some fixed finite quantization block length. We show that the excess coding…

Information Theory · Computer Science 2011-02-15 Amir Ingber , Yuval Kochman

We derive a lower bound on the differential entropy of a log-concave random variable $X$ in terms of the $p$-th absolute moment of $X$. The new bound leads to a reverse entropy power inequality with an explicit constant, and to new bounds…

Information Theory · Computer Science 2018-04-04 Arnaud Marsiglietti , Victoria Kostina

We refine and extend Ziv's model and results regarding perfectly secure encryption of individual sequences. According to this model, the encrypter and the legitimate decrypter share in common a secret key, not shared with the unauthorized…

Information Theory · Computer Science 2024-05-10 Neri Merhav

We consider the rate distortion problem with side information at the decoder posed and investigated by Wyner and Ziv. The rate distortion function indicating the trade-off between the rate on the data compression and the quality of data…

Information Theory · Computer Science 2016-04-27 Yasutada Oohama

We investigate lossy compression (source coding) of data in the form of permutations. This problem has direct applications in the storage of ordinal data or rankings, and in the analysis of sorting algorithms. We analyze the rate-distortion…

Information Theory · Computer Science 2016-11-18 Da Wang , Arya Mazumdar , Gregory Wornell

We derive quantum counterparts of two key theorems of classical information theory, namely, the rate distortion theorem and the source-channel separation theorem. The rate-distortion theorem gives the ultimate limits on lossy data…

Quantum Physics · Physics 2012-12-21 Nilanjana Datta , Min-Hsiu Hsieh , Mark M. Wilde

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

It was recently shown that the lossless compression of a single source $X^n$ is achievable with a notion of strong locality; any $X_i$ can be decoded from a constant number of compressed bits, with a vanishing in $n$ probability of error.…

Information Theory · Computer Science 2022-09-28 Shashank Vatedka , Venkat Chandar , Aslan Tchamkerten

A general method of source coding over expansion is proposed in this paper, which enables one to reduce the problem of compressing an analog (continuous-valued source) to a set of much simpler problems, compressing discrete sources.…

Information Theory · Computer Science 2013-08-13 Hongbo Si , O. Ozan Koyluoglu , Sriram Vishwanath

Lossy compression algorithms are typically designed to achieve the lowest possible distortion at a given bit rate. However, recent studies show that pursuing high perceptual quality would lead to increase of the lowest achievable distortion…

Information Theory · Computer Science 2021-06-15 Zeyu Yan , Fei Wen , Rendong Ying , Chao Ma , Peilin Liu

Shannon showed that to achieve perfect secrecy in point-to-point communication, the message rate cannot exceed the shared secret key rate giving rise to the simple one-time pad encryption scheme. In this paper, we extend this work from…

Information Theory · Computer Science 2020-05-29 Hongchao Zhou , Abbas El Gamal

Shannon's secrecy system is studied in a setting, where both the legitimate decoder and the wiretapper have access to side information sequences correlated to the source, but the wiretapper receives both the coded information and the side…

Information Theory · Computer Science 2007-07-13 Neri Merhav

We apply statistical mechanics to an inverse problem of linear mapping to investigate the physics of the irreversible compression. We use the replica symmetry breaking (RSB) technique with a toy model to demonstrate the Shannon's result.…

Disordered Systems and Neural Networks · Physics 2009-11-07 Tatsuto Murayama , Masato Okada

Shannon's channel coding theorem describes the maximum possible rate of reliable information transfer through a classical noisy communication channel. It, together with the source coding theorem, characterizes lossless channel communication…

Quantum Physics · Physics 2021-05-17 Sristy Agrawal , Rajashik Tarafder , Graeme Smith , Arup Roy , Manik Banik

We study a new encoding scheme for lossy source compression based on spatially coupled low-density generator-matrix codes. We develop a belief-propagation guided-decimation algorithm, and show that this algorithm allows to approach the…

Information Theory · Computer Science 2012-02-23 Vahid Aref , Nicolas Macris , Rudiger Urbanke , Marc Vuffray

Recent advances in machine learning-aided lossy compression are incorporating perceptual fidelity into the rate-distortion theory. In this paper, we study the rate-distortion-perception trade-off when the perceptual quality is measured by…

Information Theory · Computer Science 2023-05-23 Xueyan Niu , Deniz Gündüz , Bo Bai , Wei Han

The $\epsilon$-machine is a stochastic process' optimal model -- maximally predictive and minimal in size. It often happens that to optimally predict even simply-defined processes, probabilistic models -- including the $\epsilon$-machine --…

Statistical Mechanics · Physics 2021-12-15 Alexandra M. Jurgens , James P. Crutchfield

Locally decodable channel codes form a special class of error-correcting codes with the property that the decoder is able to reconstruct any bit of the input message from querying only a few bits of a noisy codeword. It is well known that…

Information Theory · Computer Science 2013-08-28 Ali Makhdoumi , Shao-Lun Huang , Muriel Medard , Yury Polyanskiy

We study the following semi-deterministic setting of the joint source-channel coding problem: a deterministic source sequence (a.k.a. individual sequence) is transmitted via a memoryless channel, using delay-limited encoder and decoder,…

Information Theory · Computer Science 2021-09-29 Neri Merhav

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
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