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The chordal ring (CR) graphs are a well-known family of graphs used to model some interconnection networks for computer systems in which all nodes are in a cycle. Generalizing the CR graphs, in this paper, we introduce the families of…

Combinatorics · Mathematics 2024-09-04 M. A. Reyes , C. Dalfó , M. A. Fiol

We study noncommutative differential structures on the group of permutations $S_N$, defined by conjugacy classes. The 2-cycles class defines an exterior algebra $\Lambda_N$ which is a super analogue of the Fomin-Kirillov algebra $\CE_N$ for…

Quantum Algebra · Mathematics 2007-05-23 Shahn Majid

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, a class of three-weight…

Information Theory · Computer Science 2013-02-05 Zhengchun Zhou , Cunsheng Ding

We consider diffeomorphisms $f$ with heterodimensional cycles of co-index two, associated with saddles $P$ and $Q$ having unstable indices $\ell$ and $\ell+2$, respectively. In a partially hyperbolic setting, where a two-dimensional center…

Dynamical Systems · Mathematics 2025-11-18 Pablo G. Barrientos , Lorenzo J. Díaz , Yuri Ki , Cristina Lizana , Sebastián A. Pérez

We determine precisely when the branching coefficients arising from the restriction of irreducible representations of the symmetric group $S_n$ to the dihedral subgroup $D_n$ are nonzero, and we establish uniform linear lower bounds outside…

Representation Theory · Mathematics 2025-12-17 Velmurugan S

We leverage neural networks as universal approximators of monotonic functions to build a parameterization of conditional cumulative distribution functions (CDFs). By the application of automatic differentiation with respect to response…

Machine Learning · Statistics 2020-06-09 Pawel Chilinski , Ricardo Silva

We describe \textit{deep exponential families} (DEFs), a class of latent variable models that are inspired by the hidden structures used in deep neural networks. DEFs capture a hierarchy of dependencies between latent variables, and are…

Machine Learning · Statistics 2014-11-11 Rajesh Ranganath , Linpeng Tang , Laurent Charlin , David M. Blei

We present a family of quantum stabilizer codes using the structure of duadic constacyclic codes over $\mathbb{F}_4$. Within this family, quantum codes can possess varying dimensions, and their minimum distances are lower bounded by a…

Information Theory · Computer Science 2024-05-28 Reza Dastbasteh , Josu Etxezarreta Martinez , Andrew Nemec , Antonio deMarti iOlius , Pedro Crespo Bofill

This paper introduces a new approach for the computation of electromagnetic field derivatives, up to any order, with respect to the material and geometric parameters of a given geometry, in a single Finite-Difference Time-Domain (FDTD)…

Numerical Analysis · Mathematics 2024-12-20 Kae-An Liu , Hans-Dieter Lang , Costas D. Sarris

In this paper, we study skew frame starters, which are strong frame starters that satisfy an additional "skew" property. We prove three new non-existence results for cyclic skew frame starters of certain types. We also construct several…

Combinatorics · Mathematics 2022-11-23 Douglas R. Stinson

Divisibility sequences are defined by the property that their elements divide each other whenever their indices do. The divisibility sequences that also satisfy a linear recurrence, like the Fibonacci numbers, are generated by polynomials…

Number Theory · Mathematics 2022-06-22 Sergiy Koshkin

In this work, we study cyclic codes that have generators as Fibonacci polynomials over finite fields. We show that these cyclic codes in most cases produce families of maximum distance separable and optimal codes with interesting…

Information Theory · Computer Science 2017-09-25 Mehmet E. Koroglu , Ibrahim Ozbek , Irfan Siap

We relate the structure of cyclotomic and degenerate cyclotomic BMW algebras, for arbitrary parameter values, to that for admissible parameter values. In particular, we show that these algebras are cellular. We characterize those parameter…

Representation Theory · Mathematics 2012-05-09 Frederick M. Goodman

We consider a class of discontinuous piecewise linear differential systems in $\mathbb{R}^3$ with two pieces separated by a plane. In this class we show that there exist differential systems having: a unique limit cycle, a unique…

Dynamical Systems · Mathematics 2017-08-25 Bruno Rodrigues de Freitas , João Carlos Medrado

The alternate row and column scaling algorithm applied to a positive $n\times n$ matrix $A$ converges to a doubly stochastic matrix $S(A)$, sometimes called the \emph{Sinkhorn limit} of $A$. For every positive integer $n$, a two parameter…

Number Theory · Mathematics 2020-04-17 Melvyn B. Nathanson

Cyclic codes are an important subclass of linear codes with wide applications in communication systems and data storage systems. In 2013, Ding and Helleseth presented nine open problems on optimal ternary cyclic codes $\mathcal{C}_{(1,e)}$.…

Information Theory · Computer Science 2026-01-21 Jingjun Bao , Hanlin Zou

Due to their efficient encoding and decoding algorithms cyclic codes, a subclass of linear codes, have applications in consumer electronics, data storage systems, and communication systems. In this paper, Dickson polynomials of the first…

Information Theory · Computer Science 2016-11-18 Cunsheng Ding

We construct a family of (n,k) convolutional codes with degree \delta in {k,n-k} that have a maximum distance profile. The field size required for our construction is of the order n^{2\delta}, which improves upon the known constructions of…

Information Theory · Computer Science 2021-12-09 Zitan Chen

For a high-rate case, it is difficult to randomly construct good low-density parity-check (LDPC) codes of short and moderate lengths because their Tanner graphs are prone to making short cycles. Also, the existing high-rate quasi-cyclic…

Information Theory · Computer Science 2016-11-18 Hosung Park , Seokbeom Hong , Jong-Seon No , Dong-Joon Shin

The focus of this paper is on intrinsic methods to detect overfitting. By intrinsic methods, we mean methods that rely only on the model and the training data, as opposed to traditional methods (we call them extrinsic methods) that rely on…

Machine Learning · Computer Science 2020-08-07 Satrajit Chatterjee , Alan Mishchenko