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Non-binary low-density parity-check codes are robust to various channel impairments. However, based on the existing decoding algorithms, the decoder implementations are expensive because of their excessive computational complexity and…

Information Theory · Computer Science 2016-11-18 Chung-Li Wang , Xiaoheng Chen , Zongwang Li , Shaohua Yang

We present a new family of low-density parity-check (LDPC) convolutional codes that can be designed using ordered sets of progressive differences. We study their properties and define a subset of codes in this class that have some desirable…

Information Theory · Computer Science 2012-12-21 Marco Baldi , Marco Bianchi , Giovanni Cancellieri , Franco Chiaraluce

It is proved in this work that exhaustively determining bad patterns in arbitrary, finite low-density parity-check (LDPC) codes, including stopping sets for binary erasure channels (BECs) and trapping sets (also known as near-codewords) for…

Information Theory · Computer Science 2007-07-13 Chih-Chun Wang , Sanjeev R. Kulkarni , H. Vincent Poor

In this paper, we present a new approach for the analysis of iterative node-based verification-based (NB-VB) recovery algorithms in the context of compressive sensing. These algorithms are particularly interesting due to their low…

Information Theory · Computer Science 2011-06-02 Yaser Eftekhari , Anoosheh Heidarzadeh , Amir H. Banihashemi , Ioannis Lambadaris

In this paper, we consider a few iterative decoding schemes for the joint source-channel coding of correlated sources. Specifically, we consider the joint source-channel coding of two erasure correlated sources with transmission over…

Information Theory · Computer Science 2009-10-08 Arvind Yedla , Henry D. Pfister , Krishna R. Narayanan

In this paper, we present a new approach for the analysis of iterative node-based verification-based (NB-VB) recovery algorithms in the context of compressive sensing. These algorithms are particularly interesting due to their low…

Information Theory · Computer Science 2011-04-04 Yaser Eftekhari , Anoosheh Heidarzadeh , Amir H. Banihashemi , Ioannis Lambadaris

The equivalence of peeling decoding (PD) and Belief Propagation (BP) for low-density parity-check (LDPC) codes over the binary erasure channel is analyzed. Modifying the scheduling for PD, it is shown that exactly the same variable nodes…

Information Theory · Computer Science 2016-04-19 Markus Stinner , Luca Barletta , Pablo M. Olmos

Polar codes were introduced in 2009 and proven to achieve the symmetric capacity of any binary-input discrete memoryless channel under low-complexity successive cancellation decoding. In this thesis, we construct cyclic polar codes based on…

Information Theory · Computer Science 2020-04-16 Narayanan Rengaswamy

Ordinary differential equations (ODEs), via their induced flow maps, provide a powerful framework to parameterize invertible transformations for the purpose of representing complex probability distributions. While such models have achieved…

Statistics Theory · Mathematics 2023-09-06 Youssef Marzouk , Zhi Ren , Sven Wang , Jakob Zech

In this paper we study the iterative decoding threshold performance of non-binary spatially-coupled low-density parity-check (NB-SC-LDPC) code ensembles for both the binary erasure channel (BEC) and the binary-input additive white Gaussian…

Information Theory · Computer Science 2016-11-18 Lai Wei , Toshiaki Koike-Akino , David G. M. Mitchell , Thomas E. Fuja , Daniel J. Costello

Discrete diffusion has become a leading framework for generative modeling in various applications including language, vision, and biology. Existing convergence theory, however, exhibits fundamental limitations. KL-based analyses diverge…

Machine Learning · Computer Science 2026-05-19 Kelvin Kan , Xingjian Li , Benjamin J. Zhang , Tuhin Sahai , Stanley Osher , Markos A. Katsoulakis

Most existing works on analyzing the performance of a random ensemble of low-density parity-check (LDPC) codes assume that the degree distributions of the two ends of a randomly selected edge are independent. In the paper, we take one step…

Information Theory · Computer Science 2023-04-20 Hsiao-Wen Yu , Cheng-En Lee , Ruhui Zhang , Cheng-Shang Chang , Duan-Shin Lee

A decoding algorithm for $q$-ary low-density parity-check codes over the $q$-ary symmetric channel is introduced. The exchanged messages are lists of symbols from $\Fq$. A density evolution analysis for maximum list sizes $1$ and $2$ is…

Information Theory · Computer Science 2021-04-14 Emna Ben Yacoub

The design of optimal linear block codes capable of being efficiently decoded is of major concern, especially for short block lengths. As near capacity-approaching codes, Low-Density Parity-Check (LDPC) codes possess several advantages over…

Information Theory · Computer Science 2024-10-11 Yoni Choukroun , Lior Wolf

The paper introduces the weighted convolution, a novel approach to the convolution for signals defined on regular grids (e.g., 2D images) through the application of an optimal density function to scale the contribution of neighbouring…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Simone Cammarasana , Giuseppe Patanè

Bayesian density deconvolution using nonparametric prior distributions is a useful alternative to the frequentist kernel based deconvolution estimators due to its potentially wide range of applicability, straightforward uncertainty…

Statistics Theory · Mathematics 2013-09-10 Abhra Sarkar , Debdeep Pati , Bani K. Mallick , Raymond J. Carroll

We introduce a new family of concatenated codes with an outer low-density parity-check (LDPC) code and an inner low-density generator matrix (LDGM) code, and prove that these codes can achieve capacity under any memoryless binary-input…

Information Theory · Computer Science 2016-08-31 Chun-Hao Hsu , Achilleas Anastasopoulos

The quantization of the output of a binary-input discrete memoryless channel to a smaller number of levels is considered. An algorithm which finds an optimal quantizer, in the sense of maximizing mutual information between the channel input…

Information Theory · Computer Science 2014-05-16 Brian M. Kurkoski , Hideki Yagi

Spatially coupled low-density parity-check codes show an outstanding performance under the low-complexity belief propagation (BP) decoding algorithm. They exhibit a peculiar convergence phenomenon above the BP threshold of the underlying…

Information Theory · Computer Science 2013-07-16 Vahid Aref , Laurent Schmalen , Stephan ten Brink

The denoising diffusion probabilistic model (DDPM) has emerged as a mainstream generative model in generative AI. While sharp convergence guarantees have been established for the DDPM, the iteration complexity is, in general, proportional…

Machine Learning · Computer Science 2026-02-17 Zhihan Huang , Yuting Wei , Yuxin Chen
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