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Abstract: In this article, we will analyze in detail the coding limit of an individual sequence by introducing the latest developments brought by the Set Shaping Theory. This new theory made us realize that there is a huge difference…

Information Theory · Computer Science 2023-05-09 Aida Koch , Alix Petit

Set Shaping Theory (SST) moves beyond the classical fixed-space model by constructing bijective mappings the original sequence set into structured regions of a larger sequence space. These shaped subsets are characterized by a reduced…

Information Theory · Computer Science 2026-01-23 A. Schmidt , A. Vdberg , A. Petit

We study the following one-way asymmetric transmission problem, also a variant of model-based compressed sensing: a resource-limited encoder has to report a small set $S$ from a universe of $N$ items to a more powerful decoder (server). The…

Data Structures and Algorithms · Computer Science 2018-07-30 Alexandr Andoni , Javad Ghaderi , Daniel Hsu , Dan Rubenstein , Omri Weinstein

In developing locally testable codes, information is added to the coded message by creating redundancy in the codewords. In this article, we propose an alternative method in which redundancy is introduced on the message that must be…

Information Theory · Computer Science 2022-03-01 Solomon Kozlov

We consider the lossless compression bound of any individual data sequence. If we fit the data by a parametric model, the entropy quantity $nH({\hat \theta}_n)$ obtained by plugging in the maximum likelihood estimate is an underestimate of…

Information Theory · Computer Science 2024-01-23 Lei M Li

To render a sequence testable, namely capable of identifying and detecting errors, it is necessary to apply a transformation that increases its length by introducing statistical dependence among symbols, as commonly exemplified by the…

Information Theory · Computer Science 2025-07-08 Aida Koch , Alix Petit

In this paper, we propose {\em distributed network compression via memory}. We consider two spatially separated sources with correlated unknown source parameters. We wish to study the universal compression of a sequence of length $n$ from…

Information Theory · Computer Science 2012-10-09 Ahmad Beirami , Faramarz Fekri

Motivated by the problem of the definition of a distance between two sequences of characters, we investigate the so-called learning process of typical sequential data compression schemes. We focus on the problem of how a compression…

Statistical Mechanics · Physics 2009-11-07 A. Puglisi , D. Benedetto , E. Caglioti , V. Loreto , A. Vulpiani

Adaptive variable-length codes associate a variable-length codeword to the symbol being encoded depending on the previous symbols in the input string. This class of codes has been recently presented in [Dragos Trinca, arXiv:cs.DS/0505007]…

Data Structures and Algorithms · Computer Science 2007-05-23 Dragos Trinca

This paper proposes a novel entropy encoding technique for lossless data compression. Representing a message string by its lexicographic index in the permutations of its symbols results in a compressed version matching Shannon entropy of…

Information Theory · Computer Science 2017-03-24 Abu Bakar Siddique

In this paper, we consider the problem of efficiently representing a set $S$ of $n$ items out of a universe $U=\{0,...,u-1\}$ while supporting a number of operations on it. Let $G=g_1...g_n$ be the gap stream associated with $S$, $gap$ its…

Data Structures and Algorithms · Computer Science 2015-05-15 Nicola Prezza

There is a class of entropy-coding methods which do not substitute symbols by code words (such as Huffman coding), but operate on intervals or ranges. This class includes three prominent members: conventional arithmetic coding, range…

Information Theory · Computer Science 2025-07-04 Tilo Strutz , Nico Schreiber

Data compression algorithms are generally perceived as being of interest for data communication and storage purposes only. However, their use in the field of data classification and analysis is also of equal importance. Automatic data…

We discuss algorithms for estimating the Shannon entropy h of finite symbol sequences with long range correlations. In particular, we consider algorithms which estimate h from the code lengths produced by some compression algorithm. Our…

Statistical Mechanics · Physics 2017-04-24 Thomas Schürmann , Peter Grassberger

This thesis concerns sequential-access data compression, i.e., by algorithms that read the input one or more times from beginning to end. In one chapter we consider adaptive prefix coding, for which we must read the input character by…

Information Theory · Computer Science 2009-02-03 Travis Gagie

We present a data structure that stores a sequence $s[1..n]$ over alphabet $[1..\sigma]$ in $n\Ho(s) + o(n)(\Ho(s){+}1)$ bits, where $\Ho(s)$ is the zero-order entropy of $s$. This structure supports the queries \access, \rank\ and \select,…

Data Structures and Algorithms · Computer Science 2012-04-03 Jeremy Barbay , Francisco Claude , Travis Gagie , Gonzalo Navarro , Yakov Nekrich

The problem of compression in standard information theory consists of assigning codes as short as possible to numbers. Here we consider the problem of optimal coding -- under an arbitrary coding scheme -- and show that it predicts Zipf's…

Computation and Language · Computer Science 2020-09-24 Ramon Ferrer-i-Cancho , Christian Bentz , Caio Seguin

Universal compression of patterns of sequences generated by independently identically distributed (i.i.d.) sources with unknown, possibly large, alphabets is investigated. A pattern is a sequence of indices that contains all consecutive…

Information Theory · Computer Science 2016-11-17 Gil I. Shamir

Huffman Compression, also known as Huffman Coding, is one of many compression techniques in use today. The two important features of Huffman coding are instantaneousness that is the codes can be interpreted as soon as they are received and…

Information Theory · Computer Science 2013-02-22 A. S. Tolba , M. Z. Rashad , M. A. El-Dosuky

Shaping codes are used to generate code sequences in which the symbols obey a prescribed probability distribution. They arise naturally in the context of source coding for noiseless channels with unequal symbol costs. Recently, shaping…

Information Theory · Computer Science 2022-05-10 Yi Liu , Yonglong Li , Pengfei Huang , Paul H. Siegel
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