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We present a novel algorithm that solves the turbo code LP decoding problem in a fininte number of steps by Euclidean distance minimizations, which in turn rely on repeated shortest path computations in the trellis graph representing the…

Information Theory · Computer Science 2014-03-18 Michael Helmling , Stefan Ruzika

An efficient decoding algorithm for horizontally u-interleaved LRPC codes is proposed and analyzed. Upper bounds on the decoding failure rate and the computational complexity of the algorithm are derived. It is shown that interleaving…

Information Theory · Computer Science 2019-08-29 Julian Renner , Thomas Jerkovits , Hannes Bartz

Robust visual place recognition (VPR) requires scene representations that are invariant to various environmental challenges such as seasonal changes and variations due to ambient lighting conditions during day and night. Moreover, a…

Computer Vision and Pattern Recognition · Computer Science 2017-09-26 Unnat Jain , Vinay P. Namboodiri , Gaurav Pandey

In this note we first review the classical Petterson-Gorenstein-Zierler decoding algorithm for the class of alternant codes (which includes Reed-Solomon, Bose-Chaudhuri-Hocquenghem and classical Goppa codes), then we present an improvement…

Information Theory · Computer Science 2018-05-08 R. Farré , N. Sayols , S. Xambó-Descamps

This paper investigates the concept of self-dual convolutional code. We derive the basic properties of this interesting class of codes and we show how some of the techniques to construct self-dual linear block codes generalize to self-dual…

Information Theory · Computer Science 2022-08-09 Sebastian Heri , Julia Lieb , Joachim Rosenthal

We consider a windowed decoding scheme for LDPC convolutional codes that is based on the belief-propagation (BP) algorithm. We discuss the advantages of this decoding scheme and identify certain characteristics of LDPC convolutional code…

Information Theory · Computer Science 2016-11-17 Aravind Iyengar , Marco Papaleo , Paul Siegel , Jack Wolf , Alessandro Vanelli-Coralli , Giovanni Corazza

In this paper we introduce a variant of the Syndrome Decoding Problem (SDP), that we call Restricted SDP (R-SDP), in which the entries of the searched vector are defined over a subset of the underlying finite field. We prove the…

In this paper, we extend the work of (Abbondati et al., 2024) on decoding simultaneous rational number codes by addressing two important scenarios: multiplicities and the presence of bad primes (divisors of denominators). First, we…

Information Theory · Computer Science 2025-06-06 Matteo Abbondati , Eleonora Guerrini , Romain Lebreton

In [4] we describe a variation of the classical permutation decoding algorithm that can be applied to any binary affine-invariant code; in particular, it can be applied to first-order Reed-Muller codes successfully. In this paper we study…

Information Theory · Computer Science 2025-09-16 José Joaquín Bernal , Juan Jacobo Simón

An algorithm for irreducible decomposition of representations of finite groups over fields of characteristic zero is described. The algorithm uses the fact that the decomposition induces a partition of the invariant inner product into a…

Representation Theory · Mathematics 2019-06-05 Vladimir V Kornyak

There are two gradient descent decoding procedures for binary codes proposed independently by Liebler and by Ashikhmin and Barg. Liebler in his paper mentions that both algorithms have the same philosophy but in fact they are rather…

Information Theory · Computer Science 2010-08-27 M. Borges Quintana , M. A. Borges Trenard , I. Marquez-Corbella , E. Martinez-Moro

Random Linear Network Coding (RLNC) provides a theoretically efficient method for coding. Some of its practical drawbacks are the complexity of decoding and the overhead due to the coding vectors. For computationally weak and battery-driven…

Networking and Internet Architecture · Computer Science 2015-09-16 Janus Heide , Morten V. Pedersen , Frank H. P. Fitzek , Muriel M edard

Polar codes have received growing attention in the past decade and have been selected as the coding scheme for the control channel in the fifth generation (5G) wireless communication systems. However, the conventional polar codes have only…

Information Theory · Computer Science 2023-01-26 Hossein Rezaei , Nandana Rajatheva , Matti Latva-aho

This paper proposes a rate-profile construction method for polarization-adjusted convolutional (PAC) codes of any code length and rate, which is capable of maintaining trade-off between the error-correction performance and decoding…

Information Theory · Computer Science 2021-06-16 Mohsen Moradi , Amir Mozammel

Latent variable conditional models, including the latent conditional random fields as a special case, are popular models for many natural language processing and vision processing tasks. The computational complexity of the exact…

Artificial Intelligence · Computer Science 2014-06-19 Xu Sun

We propose a novel optimization-based decoding algorithm for LDPC-coded massive MIMO channels. The proposed decoding algorithm is based on a proximal gradient method for solving an approximate maximum a posteriori (MAP) decoding problem.…

Information Theory · Computer Science 2021-02-11 Tadashi Wadayama , Satoshi Takabe

An ensemble of LDPC convolutional codes with parity-check matrices composed of permutation matrices is considered. The convergence of the iterative belief propagation based decoder for terminated convolutional codes in the ensemble is…

Information Theory · Computer Science 2016-11-17 Michael Lentmaier , Arvind Sridharan , Kamil Sh. Zigangirov , Daniel J. Costello

Linear Programming (LP) decoding of Low-Density Parity-Check (LDPC) codes has attracted much attention in the research community in the past few years. The aim of LP decoding is to develop an algorithm which has error-correcting performance…

Information Theory · Computer Science 2010-10-05 Mayur Punekar , Mark F. Flanagan

In this work, we introduce a framework to study the effect of random operations on the combinatorial list-decodability of a code. The operations we consider correspond to row and column operations on the matrix obtained from the code by…

Information Theory · Computer Science 2014-08-12 Atri Rudra , Mary Wootters

This paper proposes a fractional order gradient method for the backward propagation of convolutional neural networks. To overcome the problem that fractional order gradient method cannot converge to real extreme point, a simplified…

Optimization and Control · Mathematics 2020-01-07 Dian Sheng , Yiheng Wei , Yuquan Chen , Yong Wang
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