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In this paper, we introduce a deep learning-based decoder designed for concatenated coding schemes over a deletion/substitution channel. Specifically, we focus on serially concatenated codes, where the outer code is either a convolutional…

Information Theory · Computer Science 2024-10-15 E. Uras Kargı , Tolga M. Duman

Binary embedding of high-dimensional data requires long codes to preserve the discriminative power of the input space. Traditional binary coding methods often suffer from very high computation and storage costs in such a scenario. To…

Machine Learning · Statistics 2014-05-14 Felix X. Yu , Sanjiv Kumar , Yunchao Gong , Shih-Fu Chang

The computational complexity of the Maximum Likelihood decoding algorithm in [1], [2] for orthogonal space-time block codes is smaller than specified.

Information Theory · Computer Science 2009-08-08 Ender Ayanoglu

Motivated by polymer-based data-storage platforms that use chains of binary synthetic polymers as the recording media and read the content via tandem mass spectrometers, we propose a new family of codes that allows for unique string…

Information Theory · Computer Science 2019-04-22 Srilakshmi Pattabiraman , Ryan Gabrys , Olgica Milenkovic

For the past decades, linear codes with few weights have been widely studied, since they have applications in space communications, data storage and cryptography. In this paper, a class of binary linear codes is constructed and their weight…

Information Theory · Computer Science 2016-02-03 Fei Li , Yang Yan , Qiuyan Wang , Tongjiang Yan

This paper studies the geometry of binary hyperdimensional computing (HDC), a computational scheme in which data are encoded using high-dimensional binary vectors. We establish a result about the similarity structure induced by the HDC…

Machine Learning · Computer Science 2024-04-29 Saeid Pourmand , Wyatt D. Whiting , Alireza Aghasi , Nicholas F. Marshall

The article explores an encoding and structural information processing approach using sparse bit vectors and fixed-length linear vectors. The following are presented: a discrete method of speculative stochastic dimensionality reduction of…

Machine Learning · Computer Science 2025-08-05 Dmitriy Kashitsyn , Dmitriy Shabanov

Guess & Check (GC) codes are systematic binary codes that can correct multiple deletions, with high probability. GC codes have logarithmic redundancy in the length of the message $k$, and the encoding and decoding algorithms of these codes…

Information Theory · Computer Science 2019-05-01 Serge Kas Hanna , Salim El Rouayheb

In this work we will present algorithms for decoding rank metric codes. First we will look at a new decoding algorithm for Gabidulin codes using the property of Dickson matrices corresponding to linearized polynomials. We will be using a…

Information Theory · Computer Science 2018-02-01 Tovohery Hajatiana Randrianarisoa

The multidimensional convolutional codes are an extension of the notion of convolutional codes (CCs) to several dimensions of time. This paper explores the class of two-dimensional convolutional codes (2D CCs) and 2D tail-biting…

Information Theory · Computer Science 2011-09-20 Liam Alfandary , Dan Raphaeli

We present an approach to showing that a linear code is resilient to random errors. We use this approach to obtain decoding results for both transitive codes and Reed-Muller codes. We give three kinds of results about linear codes in…

Information Theory · Computer Science 2025-02-27 Anup Rao , Oscar Sprumont

We introduce a new family of codes, termed weighted superimposed codes (WSCs). This family generalizes the class of Euclidean superimposed codes (ESCs), used in multiuser identification systems. WSCs allow for discriminating all bounded,…

Information Theory · Computer Science 2008-12-18 Wei Dai , Olgica Milenkovic

Divisible codes are defined by the property that codeword weights share a common divisor greater than one. They are used to design signals for communications and sensing, and this paper explores how they can be used to protect quantum…

Quantum Physics · Physics 2022-04-29 Jingzhen Hu , Qingzhong Liang , Robert Calderbank

We address the problem of converting large-scale high-dimensional image data into binary codes so that approximate nearest-neighbor search over them can be efficiently performed. Different from most of the existing unsupervised approaches…

Computer Vision and Pattern Recognition · Computer Science 2015-12-02 Tsung-Yu Lin , Tsung-Wei Ke , Tyng-Luh Liu

A textile structure is a periodic arrangement of threads in the thickened plane. A topological classification of textile structures is harder than for classical knots and links that are non-periodic and restricted to a bounded region. The…

Geometric Topology · Mathematics 2020-07-30 Matt Bright , Vitaliy Kurlin

We introduce a decomposition method for the distributed calculation of exact Euclidean Minimum Spanning Trees in high dimensions (where sub-quadratic algorithms are not effective), or more generalized geometric-minimum spanning trees of…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-05 Richard Lettich

The binary primitive BCH codes are cyclic and are constructed by choosing a subset of the cyclotomic cosets. Which subset is chosen determines the dimension, the minimum distance and the weight distribution of the BCH code. We construct…

Information Theory · Computer Science 2022-06-23 Martin Bossert , Rebekka Schulz , Sebastian Bitzer

We consider the problem of constructing deletion correcting codes over a binary alphabet and take a graph theoretic view. An $n$-bit $s$-deletion correcting code is an independent set in a particular graph. We propose constructing such a…

Information Theory · Computer Science 2012-11-20 Daniel Cullina , Ankur A. Kulkarni , Negar Kiyavash

The determination of weight distribution of cyclic codes involves evaluation of Gauss sums and exponential sums. Despite of some cases where a neat expression is available, the computation is generally rather complicated. In this note, we…

Information Theory · Computer Science 2017-03-21 Shuxing Li , Sihuang Hu , Tao Feng , Gennian Ge

We present HashEncoding, a novel autoencoding architecture that leverages a non-parametric multiscale coordinate hash function to facilitate a per-pixel decoder without convolutions. By leveraging the space-folding behaviour of hashing…

Computer Vision and Pattern Recognition · Computer Science 2022-11-30 Lukas Zhornyak , Zhengjie Xu , Haoran Tang , Jianbo Shi