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The average weight distribution of a regular low-density parity-check (LDPC) code ensemble over a finite field is thoroughly analyzed. In particular, a precise asymptotic approximation of the average weight distribution is derived for the…

信息论 · 计算机科学 2015-03-17 Shengtian Yang , Thomas Honold , Yan Chen , Zhaoyang Zhang , Peiliang Qiu

In this paper, we derive the average weight distributions for the irregular non-binary cluster low-density parity-check (LDPC) code ensembles. Moreover, we give the exponential growth rate of the average weight distribution in the limit of…

信息论 · 计算机科学 2015-06-15 Takayuki Nozaki , Masaki Maehara , Kenta Kasai , Kohichi Sakaniwa

The multi-edge type LDPC codes, introduced by Richardson and Urbanke, present the general class of structured LDPC codes. In this paper, we derive the average weight distributions of the multi-edge type LDPC code ensembles. Furthermore, we…

信息论 · 计算机科学 2015-05-19 Kenta KASAI , Tomoharu AWANO , David DECLERCQ , Charly POULLIAT , Kohichi SAKANIWA

In this paper, an expression for the asymptotic growth rate of the number of small linear-weight codewords of irregular doubly-generalized LDPC (D-GLDPC) codes is derived. The expression is compact and generalizes existing results for LDPC…

信息论 · 计算机科学 2010-05-05 Mark F. Flanagan , Enrico Paolini , Marco Chiani , Marc Fossorier

Asymptotic concentration behaviors of linear combinations of weight distributions on the random linear code ensemble are presented. Many important properties of a binary linear code can be expressed as the form of a linear combination of…

信息论 · 计算机科学 2008-03-10 Tadashi Wadayama

A solution is presented for the asymptotic growth rate of the AWGN-pseudoweight distribution of regular low-density parity-check (LDPC) code ensembles for a selected graph cover degree M >= 1. The evaluation of the growth rate requires…

信息论 · 计算机科学 2009-08-11 Mark F. Flanagan

In this paper, an expression for the asymptotic growth rate of the number of small linear-weight codewords of irregular doubly-generalized LDPC (D-GLDPC) codes is derived. The expression is compact and generalizes existing results for LDPC…

信息论 · 计算机科学 2008-08-27 Mark F. Flanagan , Enrico Paolini , Marco Chiani , Marc Fossorier

In this paper Raptor code ensembles with linear random precodes 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…

信息论 · 计算机科学 2015-04-22 Francisco Lázaro , Enrico Paolini , Gianluigi Liva , Gerhard Bauch

In this paper, redundant random matrix ensembles (abbreviated as redundant random ensembles) are defined and their stopping set (SS) weight distributions are analyzed. A redundant random ensemble consists of a set of binary matrices with…

信息论 · 计算机科学 2016-11-15 Tadashi Wadayama

A fundamental property of codes, the second-order weight distribution, is proposed to solve the problems such as computing second moments of weight distributions of linear code ensembles. A series of results, parallel to those for weight…

信息论 · 计算机科学 2011-11-15 Shengtian Yang

In this paper, the average coset weight distribution (ACWD) of structured ensembles of LDPC (Low-density Parity-Check) matrix, which is called combined ensembles, is discussed. A combined ensemble is composed of a set of simpler ensembles…

信息论 · 计算机科学 2007-07-13 Tadashi Wadayama

This paper analyzes the asymptotic exponent of the weight spectrum for irregular doubly-generalized LDPC (D-GLDPC) codes. In the process, an efficient numerical technique for its evaluation is presented, involving the solution of a 4 x 4…

信息论 · 计算机科学 2016-11-18 Mark F. Flanagan , Enrico Paolini , Marco Chiani , Marc P. C. Fossorier

The growth rate of the weight distribution of irregular doubly-generalized LDPC (D-GLDPC) codes is developed and in the process, a new efficient numerical technique for its evaluation is presented. The solution involves simultaneous…

信息论 · 计算机科学 2016-11-18 Mark F. Flanagan , Enrico Paolini , Marco Chiani , Marc P. C. Fossorier

The performance of low-density parity-check (LDPC) codes in the error floor region is closely related to some combinatorial structures of the code's Tanner graph, collectively referred to as {\it trapping sets (TSs)}. In this paper, we…

信息论 · 计算机科学 2018-06-12 Ali Dehghan , Amir H. Banihashemi

We obtain exact expressions for the asymptotic behaviour of the average probability of the block decoding error for ensembles of regular low density parity check error correcting codes, by employing diagrammatic techniques. Furthermore, we…

统计力学 · 物理学 2007-05-23 J. van Mourik , Y. Kabashima

We discuss in detail the asymptotic distribution of sample expectiles. First, we show uniform consistency under the assumption of a finite mean. In case of a finite second moment, we show that for expectiles other then the mean, only the…

统计方法学 · 统计学 2016-07-14 Hajo Holzmann , Bernhard Klar

In this paper, the minimum distance distribution of irregular generalized LDPC (GLDPC) code ensembles is investigated. Two classes of GLDPC code ensembles are analyzed; in one case, the Tanner graph is regular from the variable node…

信息论 · 计算机科学 2016-11-15 Ian P. Mulholland , Mark F. Flanagan , Enrico Paolini

In this paper, we study the cycle distribution of random low-density parity-check (LDPC) codes, randomly constructed protograph-based LDPC codes, and random quasi-cyclic (QC) LDPC codes. We prove that for a random bipartite graph, with a…

信息论 · 计算机科学 2018-02-13 Ali Dehghan , Amir H. Banihashemi

We investigate the weight distribution of random binary linear codes. For $0<\lambda<1$ and $n\to\infty$ pick uniformly at random $\lambda n$ vectors in $\mathbb{F}_2^n$ and let $C \le \mathbb{F}_2^n$ be the orthogonal complement of their…

信息论 · 计算机科学 2024-07-11 Nati Linial , Jonathan Mosheiff

We prove new lower bounds on the likely size of a maximum independent set in a random graph with a given average degree. Our method is a weighted version of the second moment method, where we give each independent set a weight based on the…

计算复杂性 · 计算机科学 2011-11-15 Varsha Dani , Cristopher Moore
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