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Related papers: Construction of LDGM lattices

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In this paper, we explore the design and analysis of regular bipartite graphs motivated by their application in low-density parity-check (LDPC) codes specifically with constrained girth and in the high-rate regime. We focus on the relation…

Information Theory · Computer Science 2025-06-16 Sheida Rabeti , Mohsen Moradi , Hessam Mahdavifar

With the rapid development of Large Language Models (LLMs), Controllable Text Generation (CTG) has become a critical technology for enhancing system reliability and user experience. Addressing the limitations of traditional methods, this…

Computation and Language · Computer Science 2025-09-23 Yan Zhuang , Yuan Sun

We propose several improvements for Linear Programming (LP) decoding algorithms for High Density Parity Check (HDPC) codes. First, we use the automorphism groups of a code to create parity check matrix diversity and to generate valid cuts…

Information Theory · Computer Science 2016-11-18 Alex Yufit , Asi Lifshitz , Yair Be'ery

This paper discusses the feasibility of using Large Language Models LLM for code generation with a particular application in designing an RISC. The paper also reviews the associated steps such as parsing, tokenization, encoding, attention…

Machine Learning · Computer Science 2024-01-22 Shadeeb Hossain , Aayush Gohil , Yizhou Wang

The construction of deletion codes for the Levenshtein metric is reduced to the construction of codes over the integers for the Manhattan metric by run length coding. The latter codes are constructed by expurgation of translates of…

Information Theory · Computer Science 2014-06-05 Lin Sok , Patrick Solé , Aslan Tchamkerten

This paper proposes a novel maximum-likelihood (ML) soft-decision decoding framework for linear block codes, termed error-building decoding (EBD). The complete decoding process can be performed using only the parity-check matrix, without…

Information Theory · Computer Science 2026-01-06 Guoda Qiu , Ling Liu , Yuejun Wei , Liping Li

Deep Generative Machine Learning Models (DGMs) have been growing in popularity across the design community thanks to their ability to learn and mimic complex data distributions. DGMs are conventionally trained to minimize statistical…

Machine Learning · Computer Science 2022-06-16 Lyle Regenwetter , Faez Ahmed

With the use of belief propagation (BP) decoding algorithm, low-density parity-check (LDPC) codes can achieve near-Shannon limit performance. In order to evaluate the error performance of LDPC codes, simulators running on CPUs are commonly…

Information Theory · Computer Science 2012-07-30 Yue Zhao , Francis C. M. Lau

This paper proposes a new method of constructing compact fully-connected Quasi-Cyclic Low Density Parity Check (QC-LDPC) codes with girth g = 8, 10, and 12. The originality of the proposed method is to impose constraints on the exponent…

Information Theory · Computer Science 2021-10-14 Alireza Tasdighi , Emmanuel Boutillon

Decoders for Low Density Parity Check (LDPC) codes are usually tailored to an application and optimized once the specific content and structure of the parity matrix are known. In this work we consider the parity matrix as an argument of the…

Information Theory · Computer Science 2025-07-15 Omer Shimon Sella , Thomas Heinis

We propose a new representation for encoding 3D shapes as neural fields. The representation is designed to be compatible with the transformer architecture and to benefit both shape reconstruction and shape generation. Existing works on…

Computer Vision and Pattern Recognition · Computer Science 2022-10-19 Biao Zhang , Matthias Nießner , Peter Wonka

In order to understand the performance of a code under maximum-likelihood (ML) decoding, one studies the codewords, in particular the minimal codewords, and their Hamming weights. In the context of linear programming (LP) decoding, one's…

Information Theory · Computer Science 2007-07-13 Roxana Smarandache , Pascal O. Vontobel

In Linear Programming (LP) decoding of a Low-Density-Parity-Check (LDPC) code one minimizes a linear functional, with coefficients related to log-likelihood ratios, over a relaxation of the polytope spanned by the codewords \cite{03FWK}. In…

Information Theory · Computer Science 2007-07-13 Michael Chertkov , Mikhail G. Stepanov

Lattice gas algorithms (LGA) are a class of algorithms including, in chronological order, binary lattice gas cellular automata (LGCA), integer lattice gas algorithms (ILGA) and lattice Boltzmann method (LBM). They are largely used for…

Quantum Physics · Physics 2025-09-04 Niccolò Fonio , Ljubomir Budinski , Valtteri Lahtinen , Pierre Sagaut

The problem of communicating over the additive white Gaussian noise (AWGN) channel with lattice codes is addressed in this paper. Theoretically, Voronoi constellations have proved to yield very powerful lattice codes when the fine/coding…

Information Theory · Computer Science 2017-08-03 Nicola di Pietro , Joseph J. Boutros

A new statistical technique for constructing linear latent structure (LLS) models from available data, supported by well established theoretical results and an efficient algorithm, is presented. The method reduces the problem of estimating…

Statistics Theory · Mathematics 2007-06-13 I. Akushevich , M. Kovtun , A. I. Yashin , K. G. Manton

In this paper, we investigate novel strategies for generating rate-compatible (RC) irregular low-density parity-check (LDPC) codes with short/moderate block lengths. We propose three puncturing and two extension schemes, which are designed…

Information Theory · Computer Science 2014-07-22 J. Liu , R. C. de Lamare

We propose a new algorithm for binary quantization based on the Belief Propagation algorithm with decimation over factor graphs of Low Density Generator Matrix (LDGM) codes. This algorithm, which we call Bias Propagation (BiP), can be…

Information Theory · Computer Science 2007-10-03 Tomas Filler , Jessica Fridrich

Large Language Models (LLMs) have demonstrated great promise in generating code, especially when used inside an evolutionary computation framework to iteratively optimize the generated algorithms. However, in some cases they fail to…

Neural and Evolutionary Computing · Computer Science 2025-03-24 Niki van Stein , Anna V. Kononova , Lars Kotthoff , Thomas Bäck

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder,…

Information Theory · Computer Science 2018-03-14 Eliya Nachmani , Elad Marciano , Loren Lugosch , Warren J. Gross , David Burshtein , Yair Beery
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