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The error coefficient of a linear code is defined as the number of minimum-weight codewords. In an additive white Gaussian noise channel, optimal linear codes with the smallest error coefficients achieve the best possible asymptotic frame…

Information Theory · Computer Science 2025-07-09 Chaofeng Guan , Shitao Li , Gaojun Luo , Zhi Ma , Hong Wang

In this paper, we propose a methodology to compute the optimal finite-length coding rate for random linear network coding schemes over a line network. To do so, we first model the encoding, reencoding, and decoding process of different…

Networking and Internet Architecture · Computer Science 2018-05-16 Tan Do-Duy , M. Ángeles Vázquez-Castro

In this article we present an algorithm to compute bounds on the marginals of a graphical model. For several small clusters of nodes upper and lower bounds on the marginal values are computed independently of the rest of the network. The…

Artificial Intelligence · Computer Science 2011-06-27 B. Kappen , M. Leisink

Energy-based models (EBMs) estimate unnormalized densities in an elegant framework, but they are generally difficult to train. Recent work has linked EBMs to generative adversarial networks, by noting that they can be trained through a…

Machine Learning · Computer Science 2025-06-06 Cong Geng , Jia Wang , Li Chen , Zhiyong Gao , Jes Frellsen , Søren Hauberg

We propose a modified iterative bounded distance decoding of product codes. The proposed algorithm is based on exchanging hard messages iteratively and exploiting channel reliabilities to make hard decisions at each iteration. Performance…

Information Theory · Computer Science 2018-05-15 Alireza Sheikh , Alexandre Graell i Amat , Gianluigi Liva

In this work, we study two types of constraints on two-dimensional binary arrays. In particular, given $p,\epsilon>0$, we study (i) The $p$-bounded constraint: a binary vector of size $m$ is said to be $p$-bounded if its weight is at most…

Information Theory · Computer Science 2022-08-22 Tuan Thanh Nguyen , Kui Cai , Han Mao Kiah , Kees A. Schouhamer Immink , Yeow Meng Chee

A constant weight binary code consists of $n$-bit binary codewords, each with exactly $w$ bits equal to 1, such that any two codewords are at least Hamming distance $d$ apart. $A(n,d,w)$ is the maximum size of a constant weight binary code…

Information Theory · Computer Science 2026-03-03 Christopher D. Rosin

A general multi-terminal source code and a general multi-terminal channel code are presented. Constrained-random-number generators with sparse matrices, which are building blocks for the code construction, are used in the construction of…

Information Theory · Computer Science 2018-01-11 Jun Muramatsu , Shigeki Miyake

Generalized bicycle (GB) codes is a class of quantum error-correcting codes constructed from a pair of binary circulant matrices. Unlike for other simple quantum code ans\"atze, unrestricted GB codes may have linear distance scaling. In…

Quantum Physics · Physics 2022-04-01 Renyu Wang , Leonid P. Pryadko

Despite the growing popularity of deep learning technologies, high memory requirements and power consumption are essentially limiting their application in mobile and IoT areas. While binary convolutional networks can alleviate these…

Computer Vision and Pattern Recognition · Computer Science 2020-08-05 Dmitry Ignatov , Andrey Ignatov

This paper studies random-coding error exponents of randomised list decoding, in which the decoder randomly selects $L$ messages with probabilities proportional to the decoding metric of the codewords. The exponents (or bounds) are given…

Information Theory · Computer Science 2026-01-15 Henrique K. Miyamoto , Sheng Yang

We present an alternative to the pseudo-inverse method for determining the hidden to output weight values for Extreme Learning Machines performing classification tasks. The method is based on linear discriminant analysis and provides Bayes…

Neural and Evolutionary Computing · Computer Science 2014-06-13 Philip de Chazal , Jonathan Tapson , André van Schaik

Recently, minimal linear codes have been extensively studied due to their applications in secret sharing schemes, secure two-party computations, and so on. Constructing minimal linear codes violating the Ashikhmin-Barg condition and then…

Information Theory · Computer Science 2022-01-11 Haibo Liu , Qunying Liao

A noisy entropy inequality for boolean functions by Samorodnitsky is applied to binary codes. It is shown that a binary code that achieves capacity on the binary erasure channel admits optimal list size for list decoding on some binary…

Information Theory · Computer Science 2022-12-06 Jan Hązła

There has been a great deal of work establishing that random linear codes are as list-decodable as uniformly random codes, in the sense that a random linear binary code of rate $1 - H(p) - \epsilon$ is $(p,O(1/\epsilon))$-list-decodable…

Information Theory · Computer Science 2020-11-26 Ray Li , Mary Wootters

Random number generators (RNG) based on quantum mechanics are captivating due to their security and unpredictability compared to conventional generators, such as pseudo-random number generators and hardware-random number generators. This…

In this paper we consider the lossy compression of a binary symmetric source. We present a scheme that provides a low complexity lossy compressor with near optimal empirical performance. The proposed scheme is based on b-reduced…

Information Theory · Computer Science 2016-11-18 Alfredo Braunstein , Farbod Kayhan , Riccardo Zecchina

We describe some pseudorandom properties of binary linear codes achieving capacity on the binary erasure channel under bit-MAP decoding (as shown in Kudekar et al this includes doubly transitive codes and, in particular, Reed-Muller codes).…

Information Theory · Computer Science 2022-06-13 Alex Samorodnitsky

We present a new bound for the minimum distance of a general primary linear code. For affine variety codes defined from generalised C_{ab} curves the new bound often improves dramatically on the Feng-Rao bound for primary codes. The method…

Information Theory · Computer Science 2013-07-25 Olav Geil , Stefano Martin

We propose a new construction for low-density source codes with multiple parameters that can be tuned to optimize the performance of the code. In addition, we introduce a set of analysis techniques for deriving upper bounds for the expected…

Information Theory · Computer Science 2007-07-13 Emin Martinian , Martin J. Wainwright