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In this paper, we use a linear programming (LP) optimization approach to evaluate the equivocation for a wiretap channel where the main channel is noiseless, and the wiretap channel is a binary symmetric channel (BSC). Using this technique,…

Information Theory · Computer Science 2024-01-17 Ali Nikkhah , Morteza Shoushtari , Bahareh Akhbari , Willie K. Harrison

In this paper we investigate the decoding of parallel turbo codes over the binary erasure channel suited for upper-layer error correction. The proposed algorithm performs on-the-fly decoding, i.e. it starts decoding as soon as the first…

Information Theory · Computer Science 2008-03-13 Ghassan M. Kraidy , Valentin Savin

We investigate adaptive single-trial error/erasure decoding of binary codes whose decoder is able to correct e errors and t erasures if le+t<=d-1. Thereby, d is the minimum Hamming distance of the code and 1<l<=2 is the tradeoff parameter…

Information Theory · Computer Science 2010-05-03 Christian Senger , Vladimir R. Sidorenko , Steffen Schober , Martin Bossert , Victor V. Zyablov

Two sharp lower bounds for the length of a longest cycle $C$ of a graph $G$ are presented in terms of the lengths of a longest path and a longest cycle of $G-C$, denoted by $\overline{p}$ and $\overline{c}$, respectively, combined with…

Combinatorics · Mathematics 2009-05-12 Zh. G. Nikoghosyan

Erd\H{o}s and Simonovits asked the following question: For an integer $r\geq 2$ and a family of non-bipartite graphs $\mathcal{H}$, determine the infimum of $\alpha$ such that any $\mathcal{H}$-free $n$-vertex graph with minimum degree at…

Combinatorics · Mathematics 2025-04-10 Xiaoli Yuan , Yuejian Peng

In this paper, we provide a new approach to the analytical estimation of the bit-error rate (BER) for convolutional codes for Viterbi decoding in the binary symmetric channel (BSC). The expressions we obtained for lower and upper BER bounds…

Information Theory · Computer Science 2022-11-22 Anastasia Kurmukova , Fedor Ivanov , Victor Zyablov

Noise in quantum computing is countered with quantum error correction. Achieving optimal performance will require tailoring codes and decoding algorithms to account for features of realistic noise, such as the common situation where the…

Quantum Physics · Physics 2020-04-02 David K. Tuckett , Stephen D. Bartlett , Steven T. Flammia , Benjamin J. Brown

In the present paper, we consider list decoding for both random rank metric codes and random linear rank metric codes. Firstly, we show that, for arbitrary $0<R<1$ and $\epsilon>0$ ($\epsilon$ and $R$ are independent), if $0<\frac{n}{m}\leq…

Information Theory · Computer Science 2014-01-24 Yang Ding

The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered. It is shown that the neural decoder can be improved with two novel loss terms on the node's activations. The first loss term imposes a…

Information Theory · Computer Science 2022-08-12 Eliya Nachmani , Yair Be'ery

The {\em acyclic chromatic number} of a graph is the least number of colors needed to properly color its vertices so that none of its cycles has only two colors. The {\em acyclic chromatic index} is the analogous graph parameter for edge…

Combinatorics · Mathematics 2024-10-15 Lefteris Kirousis , John Livieratos

We present an analytical theory of greedy peeling decoding for bivariate bicycle (BB) codes under circuit-level noise. The deferred greedy decoder achieves 330x latency reduction over belief propagation (BP) at p = 10^{-3} while maintaining…

Quantum Physics · Physics 2026-04-14 Anton Pakhunov

The maximum likelihood threshold (MLT) of a graph $G$ is the minimum number of samples to almost surely guarantee existence of the maximum likelihood estimate in the corresponding Gaussian graphical model. Recently a new characterization of…

An identifying code is a subset of vertices of a graph such that each vertex is uniquely determined by its neighbourhood within the identifying code. If $\M(G)$ denotes the minimum size of an identifying code of a graph $G$, it was…

Discrete Mathematics · Computer Science 2012-09-24 Florent Foucaud , Guillem Perarnau

This work proves new results on the ability of binary Reed-Muller codes to decode from random errors and erasures. We obtain these results by proving improved bounds on the weight distribution of Reed-Muller codes of high degrees.…

Information Theory · Computer Science 2018-12-03 Ori Sberlo , Amir Shpilka

We study analytically and numerically decoding properties of finite rate hypergraph-product quantum LDPC codes obtained from random (3,4)-regular Gallager codes, with a simple model of independent X and Z errors. Several non-trival lower…

Quantum Physics · Physics 2018-06-14 Alexey A. Kovalev , Sanjay Prabhakar , Ilya Dumer , Leonid P. Pryadko

In this work, we consider efficient maximum-likelihood decoding of linear block codes for small-to-moderate block lengths. The presented approach is a branch-and-bound algorithm using the cutting-plane approach of Zhang and Siegel (IEEE…

Information Theory · Computer Science 2014-04-29 Michael Helmling , Eirik Rosnes , Stefan Ruzika , Stefan Scholl

This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation…

Information Theory · Computer Science 2023-05-17 Ioannis Papoutsidakis , Angela Doufexi , Robert J. Piechocki

We consider a class of random loop models (including the random interchange process) that are parametrised by a time parameter $\beta\geq 0$. Intuitively, larger $\beta$ means more randomness. In particular, at $\beta=0$ we start with loops…

Probability · Mathematics 2019-08-28 Peter Mühlbacher

We derive the optimum second-order coding rates, known as second-order capacities, for erasure and list decoding. For erasure decoding for discrete memoryless channels, we show that second-order capacity is $\sqrt{V}\Phi^{-1}(\epsilon_t)$…

Information Theory · Computer Science 2014-04-22 Vincent Y. F. Tan , Pierre Moulin

We study the linear list chromatic number, denoted $\lcl(G)$, of sparse graphs. The maximum average degree of a graph $G$, denoted $\mad(G)$, is the maximum of the average degrees of all subgraphs of $G$. It is clear that any graph $G$ with…

Combinatorics · Mathematics 2011-10-12 Daniel W. Cranston , Gexin Yu
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