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Cyclic codes are a subclass of linear codes and have applications in consumer electronics, data storage systems, and communication systems as they have efficient encoding and decoding algorithms. In this paper, monomials and trinomials over…

Information Theory · Computer Science 2013-10-08 Cunsheng Ding , Zhengchun Zhou

An open convex set in real projective space is called divisible if there exists a discrete group of projective automorphisms which acts co-compactly. There are many examples of such sets and a theorem of Benoist implies that many of these…

Differential Geometry · Mathematics 2013-08-20 Andrew M. Zimmer

We consider the problem of lossless compression of binary trees, with the aim of reducing the number of code bits needed to store or transmit such trees. A lossless grammar-based code is presented which encodes each binary tree into a…

Information Theory · Computer Science 2013-04-30 Jie Zhang , En-hui Yang , John C. Kieffer

Recently, linear codes constructed by defining sets have attracted a lot of study, and many optimal linear codes with a few weights have been produced. The objective of this paper is to present a class of binary linear codes with three…

Information Theory · Computer Science 2016-08-22 Yang Yan , Fei Li , Qiuyan Wang

While faces of a polytope form a well structured lattice, in which faces of each possible dimension are present, this is not true for general compact convex sets. We address the question of what dimensional patterns are possible for the…

Metric Geometry · Mathematics 2017-03-23 Vera Roshchina , Tian Sang , David Yost

Vulnerability prediction is valuable in identifying security issues efficiently, even though it requires the source code of the target software system, which is a restrictive hypothesis. This paper presents an experimental study to predict…

Cryptography and Security · Computer Science 2025-04-01 D. Cotroneo , F. C. Grasso , R. Natella , V. Orbinato

This paper presents abstract art created by neural networks and broadly recognizable across various computer vision systems. The existence of abstract forms that trigger specific labels independent of neural architecture or training set…

Computer Vision and Pattern Recognition · Computer Science 2019-12-10 Tom White

Motivated by a wide-spread use of convex optimization techniques, convexity properties of bit error rate of the maximum likelihood detector operating in the AWGN channel are studied for arbitrary constellations and bit mappings, which also…

Information Theory · Computer Science 2010-04-16 Sergey Loyka , Francois Gagnon , Victoria Kostina

We derive a closed-form expression for the projection onto a capped rotated second-order cone -- a convex set that arises in perspective relaxations of nonlinear programs with binary indicator variables. The closed-form solution involves…

Optimization and Control · Mathematics 2025-07-16 Noam Goldberg , Ishy Zagdoun

Linear codes are widely employed in communication systems, consumer electronics, and storage devices. All linear codes over finite fields can be generated by a generator matrix. Due to this, the generator matrix approach is called a…

Information Theory · Computer Science 2016-10-21 Can Xiang

We deal with linear programming problems involving absolute values in their formulations, so that they are no more expressible as standard linear programs. The presence of absolute values causes the problems to be nonconvex and nonsmooth,…

Optimization and Control · Mathematics 2023-07-10 Milan Hladík , David Hartman

Due to some practical applications, linear complementary dual (LCD) codes and self-orthogonal codes have attracted wide attention in recent years. In this paper, we use simplicial complexes for construction of an infinite family of binary…

Information Theory · Computer Science 2020-03-18 Yansheng Wu , Yoonjin Lee

We introduce the concepts of max-closedness and numeraires of convex subsets in the nonnegative orthant of the topological vector space of all random variables built over a probability space, equipped with a topology consistent with…

Functional Analysis · Mathematics 2014-10-06 Constantinos Kardaras

Number Decision Diagrams (NDD) provide a natural finite symbolic representation for regular set of integer vectors encoded as strings of digit vectors (least or most significant digit first). The convex hull of the set of vectors…

Computational Geometry · Computer Science 2008-12-13 Alain Finkel , Jérôme Leroux

A code is called solid if, roughly speaking, any correctly-transmitted codeword in an arbitrarily corrupted string of codewords can still be decoded correctly and unambiguously. So-called variable-length solid codes, in which codewords may…

Information Theory · Computer Science 2026-03-24 Nathan Thomas Carruth

A new family of binary linear completely transitive (and, therefore, completely regular) codes is constructed. The covering radius of these codes is growing with the length of the code. In particular, for any integer r > 1, there exist two…

Information Theory · Computer Science 2013-03-12 J. Rifa , V. Zinoviev

Self-orthogonal codes are an important subclass of linear codes which have nice applications in quantum codes and lattices. It is known that a binary linear code is self-orthogonal if its every codeword has weight divisible by four, and a…

Information Theory · Computer Science 2023-11-21 Xiaoru Li , Ziling Heng

There are several methods for constructing secret sharing schemes, one of which is based on coding theory. Theoretically, every linear code can be used to construct secret sharing schemes. However, in general, determining the access…

Cryptography and Security · Computer Science 2013-09-06 Yun Song , Zhihui Li

Exact representations of real numbers such as the signed digit representation or more generally linear fractional representations or the infinite Gray code represent real numbers as infinite streams of digits. In earlier work by the first…

Logic in Computer Science · Computer Science 2021-03-26 Ulrich Berger , Dieter Spreen

Soft-thresholding has been widely used in neural networks. Its basic network structure is a two-layer convolution neural network with soft-thresholding. Due to the network's nature of nonlinearity and nonconvexity, the training process…

Machine Learning · Computer Science 2023-04-17 Chunyan Xiong , Mengli Lu , Xiaotong Yu , Jian Cao , Zhong Chen , Di Guo , Xiaobo Qu
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