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The Lempel-Ziv universal coding scheme is asymptotically optimal for the class of all stationary ergodic sources. A problem of robustness of this property under small violations of ergodicity is studied. A notion of deficiency of…

Information Theory · Computer Science 2008-06-30 V. V. V'yugin

Raptor code ensembles with linear random outer codes in a fixed-rate setting are considered. An expression for the average distance spectrum is derived and this expression is used to obtain the asymptotic exponent of the weight…

Information Theory · Computer Science 2015-11-03 Francisco Lázaro , Enrico Paolini , Gianluigi Liva , Gerhard Bauch

Sequential decoding, commonly applied to substitution channels, is a sub-optimal alternative to Viterbi decoding with significantly reduced memory costs. In this work, a sequential decoder for convolutional codes over channels that are…

Information Theory · Computer Science 2026-04-02 Anisha Banerjee , Andreas Lenz , Antonia Wachter-Zeh

We consider the following communication scenario. An encoder causally observes the Wiener process and decides when and what to transmit about it. A decoder makes real-time estimation of the process using causally received codewords. We…

Information Theory · Computer Science 2020-05-15 Nian Guo , Victoria Kostina

In the application of linear network coding to wireless broadcasting with feedback, we prove that the problem of determining the existence of an innovative encoding vector is NP-complete when the finite field size is two. When the finite…

Information Theory · Computer Science 2016-11-17 Ho Yuet Kwan , Kenneth W. Shum , Chi Wan Sung

List decoding for arbitrarily varying channels (AVCs) under state constraints is investigated. It is shown that rates within $\epsilon$ of the randomized coding capacity of AVCs with input-dependent state can be achieved under maximal error…

Information Theory · Computer Science 2009-10-06 Anand D. Sarwate , Michael Gastpar

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

The design of communication systems dedicated to machine learning tasks is one key aspect of goal-oriented communications. In this framework, this article investigates the interplay between data reconstruction and learning from the same…

Information Theory · Computer Science 2024-04-30 Jiahui Wei , Elsa Dupraz , Philippe Mary

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

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

Motivated by video coding applications, the problem of sequential coding of correlated sources with encoding and/or decoding frame-delays is studied. The fundamental tradeoffs between individual frame rates, individual frame distortions,…

Information Theory · Computer Science 2008-09-30 Nan Ma , Ye Wang , Prakash Ishwar

The network coding problem asks whether data throughput in a network can be increased using coding (compared to treating bits as commodities in a flow). While it is well-known that a network coding advantage exists in directed graphs, the…

Computational Complexity · Computer Science 2025-10-22 Mark Braverman , Zhongtian He

Slepian-Wolf theorem is a well-known framework that targets almost lossless compression of (two) data streams with symbol-by-symbol correlation between the outputs of (two) distributed sources. However, this paper considers a different…

Information Theory · Computer Science 2012-06-20 Ahmad Beirami , Faramarz Fekri

Data compression is a well-studied (and well-solved) problem in the setup of long coding blocks. But important emerging applications need to compress data to memory words of small fixed widths. This new setup is the subject of this paper.…

Information Theory · Computer Science 2017-01-12 Ori Rottenstreich , Yuval Cassuto

We provide a novel upper-bound on Witsenhausen's rate, the rate required in the zero-error analogue of the Slepian-Wolf problem; our bound is given in terms of a new information-theoretic functional defined on a certain graph. We then use…

Information Theory · Computer Science 2010-01-25 Benjamin G. Kelly , Aaron B. Wagner

A range of recent works addresses the problem of compression of sequence of tokens into a shorter sequence of real-valued vectors to be used as inputs instead of token embeddings or key-value cache. These approaches are focused on reduction…

Computation and Language · Computer Science 2025-06-24 Yuri Kuratov , Mikhail Arkhipov , Aydar Bulatov , Mikhail Burtsev

Lossy data compression lies at the heart of modern communication and storage systems. Shannon's rate-distortion theory provides the fundamental limit on how much a source can be compressed at a given fidelity, but it assumes infinitely long…

Information Theory · Computer Science 2026-03-10 Bhaskar Krishnamachari

In this paper the ensemble of codes formed by a serial concatenation of a repetition code with multiple accumulators connected through random interleavers is considered. Based on finite length weight enumerators for these codes, asymptotic…

Information Theory · Computer Science 2008-10-21 Joerg Kliewer , Kamil S. Zigangirov , Christian Koller , Daniel J. Costello

We extend the notion of list decoding to {\em ratio list decoding} which involves a list decoder whose list size is specified as a function of the number of messages $M_n$ and the block length $n$. We present necessary and sufficient…

Information Theory · Computer Science 2018-10-19 Anelia Somekh-Baruch

We show how real-number codes can be used to compress correlated sources and establish a new framework for distributed lossy source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in the…

Information Theory · Computer Science 2013-01-03 Mojtaba Vaezi , Fabrice Labeau
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