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The AWGNC, BSC, and max-fractional pseudocodeword redundancies of a binary linear code are defined to be the smallest number of rows in a parity-check matrix such that the corresponding minimum pseudoweight is equal to the minimum Hamming…

Information Theory · Computer Science 2012-03-07 Jens Zumbrägel , Vitaly Skachek , Mark F. Flanagan

We define the AWGNC, BSC, and max-fractional pseudocodeword redundancy of a code as the smallest number of rows in a parity-check matrix such that the corresponding minimum pseudoweight is equal to the minimum Hamming distance. We show that…

Information Theory · Computer Science 2010-01-12 Jens Zumbragel , Mark F. Flanagan , Vitaly Skachek

The concepts of pseudocodeword and pseudoweight play a fundamental role in the finite-length analysis of LDPC codes. The pseudoredundancy of a binary linear code is defined as the minimum number of rows in a parity-check matrix such that…

Information Theory · Computer Science 2014-10-08 Zihui Liu , Jens Zumbrägel , Marcus Greferath , Xin-Wen Wu

In order to understand the performance of a code under maximum-likelihood (ML) decoding, it is crucial to know the minimal codewords. In the context of linear programming (LP) decoding, it turns out to be necessary to know the minimal…

Information Theory · Computer Science 2016-11-17 Pascal O. Vontobel , Roxana Smarandache , Negar Kiyavash , Jason Teutsch , Dejan Vukobratovic

This paper presents new lower and upper bounds for the compression rate of binary prefix codes optimized over memoryless sources according to various nonlinear codeword length objectives. Like the most well-known redundancy bounds for…

Information Theory · Computer Science 2010-10-08 Michael B. Baer

This paper presents new lower and upper bounds for the optimal compression of binary prefix codes in terms of the most probable input symbol, where compression efficiency is determined by the nonlinear codeword length objective of…

Information Theory · Computer Science 2008-09-09 Michael Baer

We present new lower and upper bounds for the compression rate of binary prefix codes optimized over memoryless sources according to two related exponential codeword length objectives. The objectives explored here are exponential-average…

Information Theory · Computer Science 2011-05-03 Michael B. Baer

The analysis of the decoding failure rate of the bit-flipping algorithm has received increasing attention. For a binary linear code we consider the minimum number of rows in a parity-check matrix such that the bit-flipping algorithm is able…

Information Theory · Computer Science 2024-02-05 Jens Zumbrägel

Message-passing iterative decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of…

Information Theory · Computer Science 2007-07-13 Roxana Smarandache , Ali E. Pusane , Pascal O. Vontobel , Daniel J. Costello

Just as the Hamming weight spectrum of a linear block code sheds light on the performance of a maximum likelihood decoder, the pseudo-weight spectrum provides insight into the performance of a linear programming decoder. Using properties of…

Information Theory · Computer Science 2016-11-17 Panu Chaichanavong , Paul H. Siegel

In this paper we provide a method to obtain tight lower bounds on the minimum redundancy achievable by a Huffman code when the probability distribution underlying an alphabet is only partially known. In particular, we address the case where…

Information Theory · Computer Science 2019-09-04 Ian Blanes , Miguel Hernández-Cabronero , Joan Serra-Sagristà , Michael W. Marcellin

The $l$-th stopping redundancy $\rho_l(\mathcal C)$ of the binary $[n, k, d]$ code $\mathcal C$, $1 \le l \le d$, is defined as the minimum number of rows in the parity-check matrix of $\mathcal C$, such that the smallest stopping set is of…

Information Theory · Computer Science 2017-03-07 Yauhen Yakimenka , Vitaly Skachek

The trapping redundancy of a linear code is the number of rows of a smallest parity-check matrix such that no submatrix forms an $(a,b)$-trapping set. This concept was first introduced in the context of low-density parity-check (LDPC) codes…

Information Theory · Computer Science 2016-11-15 Yu Tsunoda , Yuichiro Fujiwara

It is now well known that the performance of a linear code $C$ under iterative decoding on a binary erasure channel (and other channels) is determined by the size of the smallest stopping set in the Tanner graph for $C$. Several recent…

Information Theory · Computer Science 2007-07-16 Moshe Schwartz , Alexander Vardy

The efficiency of a code is estimated by its redundancy $R$, while the complexity of a code is estimated by its average delay $\bar N$. In this work we construct word-based codes, for which $R \lesssim \bar N^{-5/3}$. Therefore, word-based…

Information Theory · Computer Science 2007-12-04 G. L. Khodak

Function-correcting codes, introduced by Lenz, Bitar, Wachter-Zeh, and Yaakobi, protect specific function values of a message rather than the entire message. A central challenge is determining the optimal redundancy -- the minimum…

Information Theory · Computer Science 2025-02-25 Gennian Ge , Zixiang Xu , Xiande Zhang , Yijun Zhang

Consider the set of source distributions within a fixed maximum relative entropy with respect to a given nominal distribution. Lossless source coding over this relative entropy ball can be approached in more than one way. A problem…

Information Theory · Computer Science 2011-05-03 Michael B. Baer , Farzad Rezaei , Charalambos D. Charalambous

Stopping sets play a crucial role in failure events of iterative decoders over a binary erasure channel (BEC). The $\ell$-th stopping redundancy is the minimum number of rows in the parity-check matrix of a code, which contains no stopping…

Information Theory · Computer Science 2018-10-02 Yauhen Yakimenka , Vitaly Skachek , Irina E. Bocharova , Boris D. Kudryashov

In order to understand the performance of a code under maximum-likelihood (ML) decoding, one studies the codewords, in particular the minimal codewords, and their Hamming weights. In the context of linear programming (LP) decoding, one's…

Information Theory · Computer Science 2007-07-13 Roxana Smarandache , Pascal O. Vontobel

Parameters of LDPC codes, such as minimum distance, stopping distance, stopping redundancy, girth of the Tanner graph, and their influence on the frame error rate performance of the BP, ML and near-ML decoding over a BEC and an AWGN channel…

Information Theory · Computer Science 2017-07-05 Irina E. Bocharova , Boris D. Kudryashov , Vitaly Skachek , Yauhen Yakimenka
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