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Related papers: Lossless Data Compression at Finite Blocklengths

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Universal source coding at short blocklengths is considered for an exponential family of distributions. The \emph{Type Size} code has previously been shown to be optimal up to the third-order rate for universal compression of all memoryless…

Information Theory · Computer Science 2016-12-21 Nematollah Iri , Oliver Kosut

This paper shows the strong converse and the dispersion of memoryless channels with cost constraints and performs refined analysis of the third order term in the asymptotic expansion of the maximum achievable channel coding rate, showing…

Information Theory · Computer Science 2015-10-09 Victoria Kostina , Sergio Verdú

An antidictionary code is a lossless compression algorithm using an antidictionary which is a set of minimal words that do not occur as substrings in an input string. The code was proposed by Crochemore et al. in 2000, and its asymptotic…

Information Theory · Computer Science 2016-11-15 Takahiro Ota , Hiroyoshi Morita

This paper considers error probabilities of random codes for memoryless channels in the fixed-rate regime. Random coding is a fundamental scheme to achieve the channel capacity and many studies have been conducted for the asymptotics of the…

Information Theory · Computer Science 2017-07-17 Junya Honda

The encoder and decoder for lossy data compression of binary memoryless sources are developed on the basis of a specific-type nonmonotonic perceptron. Statistical mechanical analysis indicates that the potential ability of the…

Information Theory · Computer Science 2009-11-11 Tadaaki Hosaka , Yoshiyuki Kabashima

The Shannon Noiseless coding theorem (the data-compression principle) asserts that for an information source with an alphabet $\mathcal X=\{0,\ldots ,\ell -1\}$ and an asymptotic equipartition property, one can reduce the number of stored…

Information Theory · Computer Science 2016-04-26 Yuri Suhov , Izabella Stuhl

Compression refers to encoding data using bits, so that the representation uses as few bits as possible. Compression could be lossless: i.e. encoded data can be recovered exactly from its representation) or lossy where the data is…

Information Theory · Computer Science 2012-10-19 Narayana Santhanam , Dharmendra Modha

In this paper, we derive non-asymptotic achievability and converse bounds on the random number generation with/without side-information. Our bounds are efficiently computable in the sense that the computational complexity does not depend on…

Information Theory · Computer Science 2016-09-28 Masahito Hayashi , Shun Watanabe

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

In this article we study lossless compression of strings of pure quantum states of indeterminate-length quantum codes which were introduced by Schumacher and Westmoreland. Past work has assumed that the strings of quantum data are prepared…

Information Theory · Computer Science 2023-03-02 George Androulakis , Duncan Wright

We present a development of parts of rate-distortion theory and pattern- matching algorithms for lossy data compression, centered around a lossy version of the Asymptotic Equipartition Property (AEP). This treatment closely parallels the…

Probability · Mathematics 2007-07-16 A. Dembo , I. Kontoyiannis

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

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

This paper focuses on the ultimate limit theory of image compression. It proves that for an image source, there exists a coding method with shapes that can achieve the entropy rate under a certain condition where the shape-pixel ratio in…

Information Theory · Computer Science 2022-12-29 Gangtao Xin , Pingyi Fan , Khaled B. Letaief

In this paper, we consider the problem of variable-length source coding allowing errors. The exponential moment of the codeword length is analyzed in the non-asymptotic regime and in the asymptotic regime. Our results show that the smooth…

Information Theory · Computer Science 2015-12-22 Shigeaki Kuzuoka

Consider a general quantum stochastic source that emits at discrete time steps quantum pure states which are chosen from a finite alphabet according to some probability distribution which may depend on the whole history. Also, fix two…

Quantum Physics · Physics 2024-12-05 George Androulakis , Rabins Wosti

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

A system of interacting qubits can be viewed as a non-i.i.d quantum information source. A possible model of such a source is provided by a quantum spin system, in which spin-1/2 particles located at sites of a lattice interact with each…

Quantum Physics · Physics 2007-07-13 Nilanjana Datta , Yuri Suhov

We consider a Shannon cipher system for memoryless sources, in which distortion is allowed at the legitimate decoder. The source is compressed using a rate distortion code secured by a shared key, which satisfies a constraint on the…

Information Theory · Computer Science 2016-11-17 Nir Weinberger , Neri Merhav

The number of random bits required to approximate a target distribution in terms of un-normalized informational divergence is considered. It is shown that for a variable-to-variable length encoder, this number is lower bounded by the…

Information Theory · Computer Science 2013-08-02 Georg Böcherer , Rana Ali Amjad