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Related papers: Hidden Markov Model Decoding for LDPC Codes

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Moderate Density Parity Check (MDPC) codes are defined here as codes which have a parity-check matrix whose row weight is $O(\sqrt{n})$ where $n$ is the length $n$ of the code. They can be decoded like LDPC codes but they decode much less…

Information Theory · Computer Science 2018-01-16 Jean-Pierre Tillich

We recently derived analytical expressions for the pairwise (auto)correlation functions (CFs) between modular layers (MLs) in close-packed structures (CPSs) for the wide class of stacking processes describable as hidden Markov models (HMMs)…

Materials Science · Physics 2014-10-21 P. M. Riechers , D. P. Varn , J. P. Crutchfield

Hidden Markov models (HMMs) are probabilistic methods in which observations are seen as realizations of a latent Markov process with discrete states that switch over time. Moving beyond standard statistical tests, HMMs offer a statistical…

Methodology · Statistics 2024-03-20 S. Mildiner Moraga , E. Aarts

Hypergraph product codes are a class of constant-rate quantum low-density parity-check (LDPC) codes equipped with a linear-time decoder called small-set-flip (SSF). This decoder displays sub-optimal performance in practice and requires very…

Quantum Physics · Physics 2021-04-21 Antoine Grospellier , Lucien Grouès , Anirudh Krishna , Anthony Leverrier

In this study, we investigate the characteristics of scheduling sequences that enable efficient decoding of generalized low-density parity-check (GLDPC) codes under the layered message-passing algorithm. In particular, we show that…

Information Theory · Computer Science 2026-04-28 Qingqing Peng , Dongxu Chang , Guiying Yan , Guanghui Wang

Linear programming (LP) decoding for low-density parity-check (LDPC) codes proposed by Feldman et al. is shown to have theoretical guarantees in several regimes and empirically is not observed to suffer from an error floor. However at low…

Information Theory · Computer Science 2016-11-18 Xishuo Liu , Stark C. Draper

We show in this work that reinforcement learning can be successfully applied to decoding short to moderate length sparse graph-based channel codes. Specifically, we focus on low-density parity check (LDPC) codes, which for example have been…

Information Theory · Computer Science 2020-10-20 Salman Habib , Allison Beemer , Joerg Kliewer

There is an increase in interest to model driving maneuver patterns via the automatic unsupervised clustering of naturalistic sequential kinematic driving data. The patterns learned are often used in transportation research areas such as…

Machine Learning · Statistics 2023-11-14 Matthew Aguirre , Wenbo Sun , Jionghua , Jin , Yang Chen

We study ensembles of codes on graphs (generalized low-density parity-check, or LDPC codes) constructed from random graphs and fixed local constrained codes, and their extension to codes on hypergraphs. It is known that the average minimum…

Information Theory · Computer Science 2011-02-22 Alexander Barg , Arya Mazumdar

For a multiple-input multiple-output (MIMO) system with unknown channel state information (CSI), a novel low-density parity check (LDPC)-coded transmission (LCT) scheme with joint pilot and data channel estimation is proposed. To fine-tune…

Information Theory · Computer Science 2023-11-14 Binghui Shi , Yongpeng Wu , Peihong Yuan , Derrick Wing Kwan Ng , Xiang-Gen Xia , Wenjun Zhang

Hidden Quantum Markov Models (HQMMs) can be thought of as quantum probabilistic graphical models that can model sequential data. We extend previous work on HQMMs with three contributions: (1) we show how classical hidden Markov models…

Machine Learning · Statistics 2017-10-26 Siddarth Srinivasan , Geoff Gordon , Byron Boots

While low-density parity-check (LDPC) codes are near capacity-achieving when paired with iterative decoders, these decoders may not output a codeword due to the existence of pseudocodewords. Thus, pseudocodewords have been studied to give…

Information Theory · Computer Science 2025-12-03 Wittawat Kositwattanarerk , Gretchen L. Matthews , Emily McMillon , Tunchanok Yutitumsatit

Non-binary low-density parity-check (LDPC) codes have some advantages over their binary counterparts, but unfortunately their decoding complexity is a significant challenge. The iterative hard- and soft-reliability based majority-logic…

Information Theory · Computer Science 2015-06-22 Chenrong Xiong , Zhiyuan Yan

It is widely accepted that quantum error correction is essential for realizing large-scale fault-tolerant quantum computing. Recent experiments have demonstrated error correction codes operating below threshold, primarily using local planar…

Quantum Physics · Physics 2026-01-21 Christian Kraglund Andersen , Eliška Greplová

Recently, hidden Markov models (HMMs) have achieved promising results for offline handwritten Chinese text recognition. However, due to the large vocabulary of Chinese characters with each modeled by a uniform and fixed number of hidden…

Computer Vision and Pattern Recognition · Computer Science 2018-08-14 Wenchao Wang , Jun Du , Zi-Rui Wang

Layered decoding is well appreciated in Low-Density Parity-Check (LDPC) decoder implementation since it can achieve effectively high decoding throughput with low computation complexity. This work, for the first time, addresses low…

Information Theory · Computer Science 2012-04-13 Zhiqiang Cui , Zhongfeng Wang , Xinmiao Zhang

This paper presents an efficient algorithm for finding the dominant trapping sets of a low-density parity-check (LDPC) code. The algorithm can be used to estimate the error floor of LDPC codes or to be part of the apparatus to design LDPC…

Information Theory · Computer Science 2012-04-16 Mehdi Karimi , Amir H. Banihashemi

We consider spatially coupled low-density parity-check (SC-LDPC) codes within a non-orthogonal interleave division multiple access (IDMA) scheme to avoid cumbersome degree profile matching of the LDPC code components to the iterative…

Information Theory · Computer Science 2019-01-29 Sebastian Cammerer , Xiaojie Wang , Yingyan Ma , Stephan ten Brink

Belief Propagation (BP) decoding of LDPC codes is extended to the case of Joint Source-Channel coding. The uncompressed source is treated as a Markov process, characterized by a transition matrix, T, which is utilized as side information…

Disordered Systems and Neural Networks · Physics 2007-05-23 Haggai Kfir , Eyal Shpilman , Ido Kanter

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