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A new finite blocklength converse for the Slepian- Wolf coding problem is presented which significantly improves on the best known converse for this problem, due to Miyake and Kanaya [2]. To obtain this converse, an extension of the linear…

Information Theory · Computer Science 2018-01-29 Sharu Theresa Jose , Ankur A. Kulkarni

Motivated by recent work on entanglement-assisted codes for sending messages over classical channels, the larger, easily characterised class of non-signalling codes is defined. Analysing the optimal performance of these codes yields an…

Quantum Physics · Physics 2016-01-01 William Matthews

Linear programming (LP) decoding approximates maximum-likelihood (ML) decoding of a linear block code by relaxing the equivalent ML integer programming (IP) problem into a more easily solved LP problem. The LP problem is defined by a set of…

Information Theory · Computer Science 2013-01-01 Xiaojie Zhang , Paul H. Siegel

Detectability of failures of linear programming (LP) decoding and the potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the underlying LP problem. In this paper, we…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi , Paul H. Siegel

In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector…

Information Theory · Computer Science 2009-11-13 Tadashi Wadayama

Linear Programming (LP) decoding of Low-Density Parity-Check (LDPC) codes has attracted much attention in the research community in the past few years. The aim of LP decoding is to develop an algorithm which has error-correcting performance…

Information Theory · Computer Science 2010-10-05 Mayur Punekar , Mark F. Flanagan

We prove a one-shot "minimax" converse bound for quantum channel coding assisted by positive partial transpose channels between sender and receiver. The bound is similar in spirit to the converse by Polyanskiy, Poor, and Verdu [IEEE Trans.…

Quantum Physics · Physics 2015-06-01 Joseph M. Renes

A linear program with linear complementarity constraints (LPCC) requires the minimization of a linear objective over a set of linear constraints together with additional linear complementarity constraints. This class has emerged as a…

Optimization and Control · Mathematics 2018-02-09 Bin Yu , John E. Mitchell , Jong-Shi Pang

We examine LDPC codes decoded using linear programming (LP). Four contributions to the LP framework are presented. First, a new method of tightening the LP relaxation, and thus improving the LP decoder, is proposed. Second, we present an…

Information Theory · Computer Science 2016-11-17 David Burshtein , Idan Goldenberg

Coordinate-wise minimization is a simple popular method for large-scale optimization. Unfortunately, for general (non-differentiable) convex problems it may not find global minima. We present a class of linear programs that coordinate-wise…

Optimization and Control · Mathematics 2020-09-15 Tomáš Dlask , Tomáš Werner

When binary linear error-correcting codes are used over symmetric channels, a relaxed version of the maximum likelihood decoding problem can be stated as a linear program (LP). This LP decoder can be used to decode error-correcting codes at…

Information Theory · Computer Science 2013-09-24 Siddharth Barman , Xishuo Liu , Stark C. Draper , Benjamin Recht

Detectability of failures of linear programming (LP) decoding and its potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the LP problem. In this paper, we make a…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi N. , Paul H. Siegel

We consider the problem of recovering a signal consisting of a superposition of point sources from low-resolution data with a cut-off frequency f. If the distance between the sources is under 1/f, this problem is not well posed in the sense…

Optimization and Control · Mathematics 2016-09-09 Carlos Fernandez-Granda

In this paper we present a finite element method for the direct transcription of constrained non-linear optimal control problems. We prove that our method converges of high order under mild assumptions. Our analysis uses a regularized…

Numerical Analysis · Mathematics 2017-12-22 Martin Peter Neuenhofen

A framework for linear-programming (LP) decoding of nonbinary linear codes over rings is developed. This framework facilitates linear-programming based reception for coded modulation systems which use direct modulation mapping of coded…

Information Theory · Computer Science 2016-11-15 Mark F. Flanagan , Vitaly Skachek , Eimear Byrne , Marcus Greferath

Linear programming (LP) relaxations are widely employed in exact solution methods for multilinear programs (MLP). One example is the family of Recursive McCormick Linearization (RML) strategies, where bilinear products are substituted for…

Optimization and Control · Mathematics 2022-07-20 Arvind U Raghunathan , Carlos Cardonha , David Bergman , Carlos J Nohra

We develop upper bounds on code size for an independent and identically distributed deletion and insertion channels for a given code length and target frame error probability. The bounds are obtained as a variation of a general converse…

Information Theory · Computer Science 2026-04-14 Ruslan Morozov , Tolga Mete Duman

A general lossless joint source-channel coding scheme based on linear codes is proposed and then analyzed in this paper. It is shown that a linear code with good joint spectrum can be used to establish limit-approaching joint source-channel…

Information Theory · Computer Science 2016-11-17 Shengtian Yang , Peiliang Qiu

Linear Programming (LP) decoding of Low-Density Parity-Check (LDPC) codes has attracted much attention in the research community in the past few years. LP decoding has been derived for binary and nonbinary linear codes. However, the most…

Information Theory · Computer Science 2016-11-17 Mayur Punekar , Pascal O. Vontobel , Mark F. Flanagan

We study a class of generalized linear programs (GLP) in a large-scale setting, which includes simple, possibly nonsmooth convex regularizer and simple convex set constraints. By reformulating (GLP) as an equivalent convex-concave min-max…

Optimization and Control · Mathematics 2023-04-10 Chaobing Song , Cheuk Yin Lin , Stephen J. Wright , Jelena Diakonikolas
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