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Many computer algebra systems have more than 1000 built-in functions, making expertise difficult. Using mock dialog boxes, this article describes a proposed interactive general-purpose wizard for organizing optional transformations and…

Symbolic Computation · Computer Science 2016-11-26 David R. Stoutemyer

In this paper, we propose to consider various models of pattern recognition. At the same time, it is proposed to consider models in the form of two operators: a recognizing operator and a decision rule. Algebraic operations are introduced…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Anvar Kabulov , Alimdzhan Babadzhanov , Islambek Saymanov

We consider evolution algebras and their related substructures: evolution ideals and evolution subalgebras. After exposing some of the concepts related to them in the literature, we explore the order structures that arise in the sets of…

Rings and Algebras · Mathematics 2025-05-06 Alejandro González Nevado

Dynamic evaluation is a paradigm in computer algebra which was introduced for computing with algebraic numbers. In linear algebra, for instance, dynamic evaluation can be used to apply programs which have been written for matrices with…

Logic in Computer Science · Computer Science 2014-11-27 Jean-Guillaume Dumas , Dominique Duval , Burak Ekici , Damien Pous

Diffusive representations of fractional differential and integral operators can provide a convenient means to construct efficient numerical algorithms for their approximate evaluation. In the current literature, many different variants of…

Numerical Analysis · Mathematics 2024-07-15 Kai Diethelm

Abbreviated Abstract: The objective of Evolutionary Computation is to solve practical problems (e.g. optimization, data mining) by simulating the mechanisms of natural evolution. This thesis addresses several topics related to adaptation…

Neural and Evolutionary Computing · Computer Science 2009-07-06 James M Whitacre

In arXiv:math/0603621 we introduced the notion of a partial translation $C^*$-algebra for a discrete metric space. Here we demonstrate that several important classical $C^*$-algebras and extensions arise naturally by considering partial…

Operator Algebras · Mathematics 2008-04-04 J. Brodzki , G. A. Niblo , N. J. Wright

The Geometric Algebra Transformer (GATr) is a versatile architecture for geometric deep learning based on projective geometric algebra. We generalize this architecture into a blueprint that allows one to construct a scalable transformer…

Machine Learning · Computer Science 2024-03-15 Pim de Haan , Taco Cohen , Johann Brehmer

This paper is a summary of the theory of discrete embeddings introduced in [5]. A discrete embedding is an algebraic procedure associating a numerical scheme to a given ordinary differential equation. Lagrangian systems possess a…

Numerical Analysis · Mathematics 2016-01-20 Loïc Bourdin , Jacky Cresson , Isabelle Greff , Pierre Inizan

We characterize normalization by evaluation as the composition of a self-interpreter with a self-reducer using a special representation scheme, in the sense of Mogensen (1992). We do so by deriving in a systematic way an untyped…

Programming Languages · Computer Science 2009-11-24 Mathieu Boespflug

We assume that every element of a matrix has a small, individual error, and model it by an external number, which is the sum of a nonstandard real number and a neutrix, the latter being a convex (external) set having the group property. The…

Rings and Algebras · Mathematics 2019-07-31 Nam van Tran , Imme van den Berg

We study structured optimization problems with polynomial objective function and polynomial equality constraints. The structure comes from a multi-grading on the polynomial ring in several variables. For fixed multi-degrees we determine the…

Optimization and Control · Mathematics 2022-09-23 Kemal Rose

This paper is a survey of our recent work on operator algebras associated to dynamical systems that lead to classification results for the systems in terms of algebraic invariants of the operator algebras.

Operator Algebras · Mathematics 2009-04-21 K. R. Davidson , E. G. Katsoulis

This work revisits operator learning from a spectral perspective by introducing Polar Linear Algebra, a structured framework based on polar geometry that combines a linear radial component with a periodic angular component. Starting from…

Machine Learning · Computer Science 2026-04-01 Giovanni Guasti

Non-linear state estimation and some related topics, like parametric estimation, fault diagnosis, and perturbation attenuation, are tackled here via a new methodology in numerical differentiation. The corresponding basic system theoretic…

Computational Engineering, Finance, and Science · Computer Science 2008-11-06 Michel Fliess , Cédric Join , Hebertt Sira-Ramirez

Examples of operator algebras with involution include the operator $*$-algebras occurring in noncommutative differential geometry studied recently by Mesland, Kaad, Lesch, and others, several classical function algebras, triangular matrix…

Operator Algebras · Mathematics 2019-02-20 David P. Blecher , Zhenhua Wang

We develop a general framework for construction and analysis of discrete extension operators with application to unfitted finite element approximation of partial differential equations. In unfitted methods so called cut elements intersected…

Numerical Analysis · Mathematics 2021-01-26 Erik Burman , Peter Hansbo , Mats G. Larson

We give a brief survey of the development of the Elliott program of classification of separable simple amenable $C^*$-algebras.

Operator Algebras · Mathematics 2023-11-27 Guihua Gong , Huaxin Lin , Zhuang Niu

We expose (without proofs) a unified computational approach to integrable structures (including recursion, Hamiltonian, and symplectic operators) based on geometrical theory of partial differential equations. We adopt a coordinate based…

Exactly Solvable and Integrable Systems · Physics 2012-07-17 Iosif Krasil'shchik , Alexander Verbovetsky , Raffaele Vitolo

We describe a neural-based method for generating exact or approximate solutions to differential equations in the form of mathematical expressions. Unlike other neural methods, our system returns symbolic expressions that can be interpreted…

Machine Learning · Computer Science 2020-11-16 Maysum Panju , Kourosh Parand , Ali Ghodsi