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This paper proposes the Symbolic-Stochastic Chase Decoding Algorithm (S-SCA) for the Reed-Solomon (RS) and BCH codes. By efficient usage of void space between constellation points for $q$-ary modulations and using soft information at the…

Information Theory · Computer Science 2017-07-17 Hossein Mani , Saied Hemati

We examine regular and irregular repeat-accumulate (RA) codes with repetition degrees which are all even. For these codes and with a particular choice of an interleaver, we give an upper bound on the decoding error probability of a…

Information Theory · Computer Science 2010-02-22 Idan Goldenberg , David Burshtein

A low-complexity tree search approach is presented that achieves the maximum-likelihood (ML) decoding performance of Reed-Muller (RM) codes. The proposed approach generates a bit-flipping tree that is traversed to find the ML decoding…

Information Theory · Computer Science 2021-07-20 Seyyed Ali Hashemi , Nghia Doan , Warren J. Gross , John Cioffi , Andrea Goldsmith

We show that Reed-Muller codes achieve capacity under maximum a posteriori bit decoding for transmission over the binary erasure channel for all rates $0 < R < 1$. The proof is generic and applies to other codes with sufficient amount of…

Information Theory · Computer Science 2015-05-22 Shrinivas Kudekar , Marco Mondelli , Eren Şaşoğlu , Rüdiger Urbanke

Automorphism Ensemble (AE) decoding has recently drawn attention as a possible alternative to list decoding of polar codes. In this letter, we investigate the distribution of Partially-Symmetric Reed-Muller (PS-RM) codes, a family of polar…

Information Theory · Computer Science 2023-08-07 Charles Pillet , Valerio Bioglio , Pascal Giard

The recent development of deep learning methods provides a new approach to optimize the belief propagation (BP) decoding of linear codes. However, the limitation of existing works is that the scale of neural networks increases rapidly with…

Information Theory · Computer Science 2021-02-11 Jincheng Dai , Kailin Tan , Zhongwei Si , Kai Niu , Mingzhe Chen , H. Vincent Poor , Shuguang Cui

In this paper we present a comprehensive framework for learning robust low-rank representations by combining and extending recent ideas for learning fast sparse coding regressors with structured non-convex optimization techniques. This…

Machine Learning · Computer Science 2012-10-01 Pablo Sprechmann , Alex M. Bronstein , Guillermo Sapiro

We present an approach to showing that a linear code is resilient to random errors. We use this approach to obtain decoding results for both transitive codes and Reed-Muller codes. We give three kinds of results about linear codes in…

Information Theory · Computer Science 2025-02-27 Anup Rao , Oscar Sprumont

This paper develops an algorithmic approach for obtaining estimates of the weight enumerators of Reed-Muller (RM) codes. Our algorithm is based on a technique for estimating the partition functions of spin systems, which in turn employs a…

Information Theory · Computer Science 2024-03-12 Shreyas Jain , V. Arvind Rameshwar , Navin Kashyap

We consider the problem of coded distributed computing where a large linear computational job, such as a matrix multiplication, is divided into $k$ smaller tasks, encoded using an $(n,k)$ linear code, and performed over $n$ distributed…

Information Theory · Computer Science 2019-06-25 Mohammad Vahid Jamali , Mahdi Soleymani , Hessam Mahdavifar

In this paper, we characterize the decoding region of algebraic soft decoding (ASD) of Reed-Solomon (RS) codes over erasure channels and binary symmetric channel (BSC). Optimal multiplicity assignment strategies (MAS) are investigated and…

Information Theory · Computer Science 2009-09-29 Jing Jiang , Krishna R. Narayanan

In this paper, we prove that the sub-field images of generalized Reed-Solomon (RS) codes can achieve the symmetric capacity of p-ary memoryless channels. Unlike the totally random linear code ensemble, as a class of maximum distance…

Information Theory · Computer Science 2025-05-14 Xiangping Zheng , Xiao Ma

The problem of sparse multichannel blind deconvolution (S-MBD) arises frequently in many engineering applications such as radar/sonar/ultrasound imaging. To reduce its computational and implementation cost, we propose a compression method…

Signal Processing · Electrical Eng. & Systems 2023-07-05 Bahareh Tolooshams , Satish Mulleti , Demba Ba , Yonina C. Eldar

We introduce a new approach to proving that a sequence of deterministic linear codes achieves capacity on an erasure channel under maximum a posteriori decoding. Rather than relying on the precise structure of the codes our method exploits…

Information Theory · Computer Science 2016-01-19 Shrinivas Kudekar , Santhosh Kumar , Marco Mondelli , Henry D. Pfister , Eren Şaşoğlu , Rüdiger Urbanke

Folded Reed-Solomon codes are an explicit family of codes that achieve the optimal trade-off between rate and error-correction capability: specifically, for any $\eps > 0$, the author and Rudra (2006,08) presented an $n^{O(1/\eps)}$ time…

Information Theory · Computer Science 2016-11-17 Venkatesan Guruswami

BiD codes, which are a new family of algebraic codes of length $3^m$, achieve the erasure channel capacity under bit-MAP decoding and offer asymptotically larger minimum distance than Reed-Muller (RM) codes. In this paper we propose fast…

Information Theory · Computer Science 2026-01-15 Devansh Jain , Lakshmi Prasad Natarajan

For many applications in signal processing and machine learning, we are tasked with minimizing a large sum of convex functions subject to a large number of convex constraints. In this paper, we devise a new random projection method (RPM) to…

Optimization and Control · Mathematics 2024-04-08 Zhichun Yang , Fu-quan Xia , Kai Tu , Man-Chung Yue

This paper introduces a new approach to proving that a sequence of deterministic linear codes achieves capacity on an erasure channel under maximum a posteriori decoding. Rather than relying on the precise structure of the codes, this…

Information Theory · Computer Science 2015-06-16 Santhosh Kumar , Henry D. Pfister

In this paper, we introduce a new way of constructing and decoding multipermutation codes. Multipermutations are permutations of a multiset that generally consist of duplicate entries. We first introduce a class of binary matrices called…

Information Theory · Computer Science 2015-07-29 Xishuo Liu , Stark C. Draper

We consider near maximum-likelihood (ML) decoding of short linear block codes. In particular, we propose a novel decoding approach based on neural belief propagation (NBP) decoding recently introduced by Nachmani et al. in which we allow a…

Information Theory · Computer Science 2020-11-30 Andreas Buchberger , Christian Häger , Henry D. Pfister , Laurent Schmalen , Alexandre Graell i Amat
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