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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…

Information Theory · Computer Science 2015-03-17 Shengtian Yang , Thomas Honold , Yan Chen , Zhaoyang Zhang , Peiliang Qiu

Recently, the weight distributions of the duals of the cyclic codes with two zeros have been obtained for several cases. In this paper we use the method developed before to solve one more special case. We make extensive use of standard…

Number Theory · Mathematics 2012-10-17 Maosheng Xiong

We propose a unified theory of generalized weights for linear codes endowed with an arbitrary distance. Instead of relying on supports or anticodes, the weights of a code are defined via the intersections of the code with a chosen family of…

Information Theory · Computer Science 2025-12-22 Andrea Di Giusto , Elisa Gorla , Alberto Ravagnani

Batch codes, introduced by Ishai, Kushilevitz, Ostrovsky and Sahai, represent the distributed storage of an $n$-element data set on $m$ servers in such a way that any batch of $k$ data items can be retrieved by reading at most one (or more…

Discrete Mathematics · Computer Science 2014-11-12 Natalia Silberstein , Anna Gál

A linear code with parameters $[n,k,n-k]$ is said to be almost maximum distance separable (AMDS for short). An AMDS code whose dual is also AMDS is referred to as an near maximum distance separable (NMDS for short) code. NMDS codes have…

Information Theory · Computer Science 2022-04-26 Xiaoru Li , Ziling Heng

We discuss some open problems concerning the maximal spread of coherent distributions. We prove a sharp bound on $\mathbb{E}|X-Y|^{\alpha}$ for $(X,Y)$ coherent and $\alpha \le 2$, and establish a novel connection between coherent…

Probability · Mathematics 2020-07-17 Stanisław Cichomski

The setting of projective systems can be used to study the parameters of a projective linear code $\mathcal{C}$. This can be done by considering the intersections of the point set $\Omega$ defined by the columns of a generating matrix for…

Combinatorics · Mathematics 2025-09-19 Angela Aguglia , Luca Giuzzi , Giovanni Longobardi , Viola Siconolfi

We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit…

Information Theory · Computer Science 2010-08-24 Yuriy A. Reznik

The Generalized Hamming weights and their relative version, which generalize the minimum distance of a linear code, are relevant to numerous applications, including coding on the wire-tap channel of type II, $t$-resilient functions,…

Information Theory · Computer Science 2024-11-21 Eduardo Camps-Moreno , Hiram H. López , Gretchen L. Matthews , Rodrigo San-José

Recently, there has been intensive research on the weight distributions of cyclic codes. In this paper, we compute the weight distributions of three classes of cyclic codes with Niho exponents. More specifically, we obtain two classes of…

Information Theory · Computer Science 2014-01-10 Shuxing Li , Tao Feng , Gennian Ge

Recent interest on permutation rank modulation shows the Kendall tau metric as an important distance metric. This note documents our first efforts to obtain upper bounds on optimal code sizes (for said metric) ala Delsarte's approach. For…

Information Theory · Computer Science 2012-06-07 Fabian Lim , Manabu Hagiwara

We construct an infinite family of two-Lee-weight and three-Lee-weight codes over the non-chain ring $\mathbb{F}_p+u\mathbb{F}_p+v\mathbb{F}_p+uv\mathbb{F}_p,$ where $u^2=0,v^2=0,uv=vu.$ These codes are defined as trace codes. They have the…

Information Theory · Computer Science 2016-12-02 Yan Liu , Minjia Shi , Patrick Solé

We study relationships between worst-case and random-noise properties of error correcting codes. More concretely, we consider connections between minimum distance, list decoding radius, and block error probability on noisy channels. A…

Information Theory · Computer Science 2026-04-06 Donald Kougang-Yombi , Jan Hązła

The random matrix uniformly distributed over the set of all m-by-n matrices over a finite field plays an important role in many branches of information theory. In this paper a generalization of this random matrix, called k-good random…

Information Theory · Computer Science 2012-05-03 Shengtian Yang , Thomas Honold

Given a binary nonlinear code, we provide a deterministic algorithm to compute its weight and distance distribution, and in particular its minimum weight and its minimum distance, which takes advantage of fast Fourier techniques. This…

Information Theory · Computer Science 2015-05-06 Emanuele Bellini , Massimiliano Sala

We consider a distributed source coding system in which several observations are communicated to the decoder using limited transmission rate. The observations must be separately coded. We introduce a robust distributed coding scheme which…

Information Theory · Computer Science 2007-07-13 Jun Chen , Toby Berger

We derive distributional limits for empirical transport distances between probability measures supported on countable sets. Our approach is based on sensitivity analysis of optimal values of infinite dimensional mathematical programs and a…

Probability · Mathematics 2018-09-18 Carla Tameling , Max Sommerfeld , Axel Munk

We introduce two new classes of covering codes in graphs for every positive integer $r$. These new codes are called local $r$-identifying and local $r$-locating-dominating codes and they are derived from $r$-identifying and…

Discrete Mathematics · Computer Science 2026-04-08 Pyry Herva , Tero Laihonen , Tuomo Lehtilä

Self-orthogonal codes are a subclass of linear codes that are contained within their dual codes. Since self-orthogonal codes are widely used in quantum codes, lattice theory and linear complementary dual (LCD) codes, they have received…

Information Theory · Computer Science 2024-11-12 Yaozong Zhang , Dabin Zheng , Xiaoqiang Wang

In distributed learning, the goal is to perform a learning task over data distributed across multiple nodes with minimal (expensive) communication. Prior work (Daume III et al., 2012) proposes a general model that bounds the communication…

Machine Learning · Computer Science 2012-04-17 Hal Daume , Jeff M. Phillips , Avishek Saha , Suresh Venkatasubramanian