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Related papers: On Sparse Regression LDPC Codes

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Recent works showed how low-density parity-check (LDPC) erasure correcting codes, under maximum likelihood (ML) decoding, are capable of tightly approaching the performance of an ideal maximum-distance-separable code on the binary erasure…

Information Theory · Computer Science 2008-04-21 Enrico Paolini , Gianluigi Liva , Michela Varrella , Balazs Matuz , Marco Chiani

Low-density parity-check codes, a class of capacity-approaching linear codes, are particularly recognized for their efficient decoding scheme. The decoding scheme, known as the sum-product, is an iterative algorithm consisting of passing…

Information Theory · Computer Science 2014-05-27 Nima Noorshams , Aravind Iyengar

In this paper, we consider the "foreach" sparse recovery problem with failure probability $p$. The goal of which is to design a distribution over $m \times N$ matrices $\Phi$ and a decoding algorithm $\algo$ such that for every…

Data Structures and Algorithms · Computer Science 2013-04-24 Anna C. Gilbert , Hung Q. Ngo , Ely Porat , Atri Rudra , Martin J. Strauss

Sparse random linear network coding (SRLNC) is an attractive technique proposed in the literature to reduce the decoding complexity of random linear network coding. Recognizing the fact that the existing SRLNC schemes are not efficient in…

Information Theory · Computer Science 2013-11-12 Kaveh Mahdaviani , Raman Yazdani , Masoud Ardakani

In this paper, a new method for decoding Low Density Parity Check (LDPC) codes, based on Multi-Layer Perceptron (MLP) neural networks is proposed. Due to the fact that in neural networks all procedures are processed in parallel, this method…

Information Theory · Computer Science 2014-11-14 Alireza Karami , Mahmoud Ahmadian Attari

This paper presents a semantic-enhanced receiver framework for transmitting natural language sentences over noisy wireless channels using multiple short block codes. After ASCII encoding, the sentence is divided into segments, each…

Information Theory · Computer Science 2026-04-30 Jiafu Hao , Chentao Yue , Wanchun Liu , Branka Vucetic , Yonghui Li

Sparse Principal Component Analysis (sPCA) is a cardinal technique for obtaining combinations of features, or principal components (PCs), that explain the variance of high-dimensional datasets in an interpretable manner. This involves…

Optimization and Control · Mathematics 2025-12-02 Ryan Cory-Wright , Jean Pauphilet

Quantum low-density parity-check (QLDPC) codes are among the most promising candidates for future quantum error correction schemes. However, a limited number of short to moderate-length QLDPC codes have been designed and their decoding…

Information Theory · Computer Science 2024-05-07 Sisi Miao , Jonathan Mandelbaum , Holger Jäkel , Laurent Schmalen

Compressive sensing (CS) is a sampling technique designed for reducing the complexity of sparse data acquisition. One of the major obstacles for practical deployment of CS techniques is the signal reconstruction time and the high storage…

Information Theory · Computer Science 2011-07-12 Wei Dai , Olgica Milenkovic , Hoa Vin Pham

We study the performance of medium-length quantum LDPC (QLDPC) codes in the depolarizing channel. Only degenerate codes with the maximal stabilizer weight much smaller than their minimum distance are considered. It is shown that with the…

Quantum Physics · Physics 2021-11-24 Pavel Panteleev , Gleb Kalachev

Product codes (PCs) and staircase codes (SCCs) are conventionally decoded based on bounded distance decoding (BDD) of the component codes and iterating between row and column decoders. The performance of iterative BDD (iBDD) can be improved…

Information Theory · Computer Science 2021-09-08 Alireza Sheikh , Alexandre Graell i Amat , Alex Alvarado

Quantum information needs to be protected by quantum error-correcting codes due to imperfect physical devices and operations. One would like to have an efficient and high-performance decoding procedure for the class of quantum stabilizer…

Quantum Physics · Physics 2023-07-18 Kao-Yueh Kuo , Ching-Yi Lai

Sparse coding is an unsupervised learning algorithm that learns a succinct high-level representation of the inputs given only unlabeled data; it represents each input as a sparse linear combination of a set of basis functions. Originally…

Machine Learning · Computer Science 2012-06-26 Roger Grosse , Rajat Raina , Helen Kwong , Andrew Y. Ng

Sparse random linear network coding (SRLNC) used as a class of erasure codes to ensure the reliability of multicast communications has been widely investigated. However, an exact expression for the decoding success probability of SRLNC is…

Information Theory · Computer Science 2021-08-27 WenLin Chen , Fang Lu , Yan Dong

Polar codes have promising error-correction capabilities. Yet, decoding polar codes is often challenging, particularly with large blocks, with recently proposed decoders based on list-decoding or neural-decoding. The former applies multiple…

Information Theory · Computer Science 2023-02-14 Tomer Raviv , Alon Goldman , Ofek Vayner , Yair Be'ery , Nir Shlezinger

We consider communication over the Gaussian multiple-access channel in the regime where the number of users grows linearly with the codelength. In this regime, schemes based on sparse superposition coding can achieve a near-optimal tradeoff…

Information Theory · Computer Science 2025-06-04 Xiaoqi Liu , Kuan Hsieh , Ramji Venkataramanan

We present a method for estimating the undetected error rate when a cyclic redundancy check (CRC) is performed on the output of the decoder of short low-density parity-check (LDPC) codes. This system is of interest for telecommand links,…

Information Theory · Computer Science 2016-11-18 Marco Baldi , Nicola Maturo , Giacomo Ricciutelli , Franco Chiaraluce

Compute-and-forward (CAF) relaying is effective to increase bandwidth efficiency of wireless two-way relay channels. In a CAF scheme, a relay is designed to decode a linear combination composed of transmitted messages from other terminals…

Information Theory · Computer Science 2018-07-05 Satoshi Takabe , Tadashi Wadayama , Masahito Hayashi

In this paper we consider the generalization of binary spatially coupled low-density parity-check (SC-LDPC) codes to finite fields GF$(q)$, $q\geq 2$, and develop design rules for $q$-ary SC-LDPC code ensembles based on their iterative…

Information Theory · Computer Science 2014-11-18 Lai Wei , David G. M. Mitchell , Thomas E. Fuja , Daniel J. Costello

While linear programming (LP) decoding provides more flexibility for finite-length performance analysis than iterative message-passing (IMP) decoding, it is computationally more complex to implement in its original form, due to both the…

Information Theory · Computer Science 2009-02-05 Mohammad H. Taghavi , Amin Shokrollahi , Paul H. Siegel
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