The general methods of finding the sum for all kinds of series
K. Orlov (1981)
Matematički Vesnik
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K. Orlov (1981)
Matematički Vesnik
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Rudolf Scitovski, Kristian Sabo (2019)
Applications of Mathematics
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We consider the multiple ellipses detection problem on the basis of a data points set coming from a number of ellipses in the plane not known in advance, whereby an ellipse is viewed as a Mahalanobis circle with center , radius , and some positive definite matrix . A very efficient method for solving this problem is proposed. The method uses a modification of the -means algorithm for Mahalanobis-circle centers. The initial approximation consists of the set of circles whose centers...
Eduardo Rangel-Heras, Pavel Zuniga, Alma Y. Alanis, Esteban A. Hernandez-Vargas, Oscar D. Sanchez (2023)
Kybernetika
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This work presents a new approach for the imputation of missing data in weather time-series from a seasonal pattern; the seasonal time-series imputation of gap missing algorithm (STIGMA). The algorithm takes advantage from a seasonal pattern for the imputation of unknown data by averaging available data. We test the algorithm using data measured every minutes over a period of days during the year 2010; the variables include global irradiance, diffuse irradiance, ultraviolet irradiance,...
Martin Grigoryan (2010)
Studia Mathematica
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For any 0 < ϵ < 1, p ≥ 1 and each function one can find a function with mesx ∈ [0,1): g ≠ f < ϵ such that its greedy algorithm with respect to the Walsh system converges uniformly on [0,1) and the sequence is decreasing, where is the sequence of Fourier coefficients of g with respect to the Walsh system.
Pierre-Louis Giscard, Stefano Pozza (2020)
Applications of Mathematics
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The time-ordered exponential of a time-dependent matrix is defined as the function of that solves the first-order system of coupled linear differential equations with non-constant coefficients encoded in . The authors have recently proposed the first Lanczos-like algorithm capable of evaluating this function. This algorithm relies on inverses of time-dependent functions with respect to a non-commutative convolution-like product, denoted by . Yet, the existence of such inverses,...
Iryna V. Fryz (2018)
Commentationes Mathematicae Universitatis Carolinae
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G. B. Belyavskaya and G. L. Mullen showed the existence of a complement for a -tuple of orthogonal -ary operations, where , to an -tuple of orthogonal -ary operations. But they proposed no method for complementing. In this article, we give an algorithm for complementing a -tuple of orthogonal -ary operations to an -tuple of orthogonal -ary operations and an algorithm for complementing a -tuple of orthogonal -ary operations to an -tuple of orthogonal -ary operations. Also...
Murray R. Bremner, Sara Madariaga, Luiz A. Peresi (2016)
Commentationes Mathematicae Universitatis Carolinae
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This is a survey paper on applications of the representation theory of the symmetric group to the theory of polynomial identities for associative and nonassociative algebras. In §1, we present a detailed review (with complete proofs) of the classical structure theory of the group algebra of the symmetric group over a field of characteristic 0 (or ). The goal is to obtain a constructive version of the isomorphism where is a partition of and counts the standard tableaux...
Zítko, Jan, Kuřátko, Jan
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The paper introduces the calculation of a greatest common divisor of two univariate polynomials. Euclid’s algorithm can be easily simulated by the reduction of the Sylvester matrix to an upper triangular form. This is performed by using - transformation and -factorization methods. Both procedures are described and numerically compared. Computations are performed in the floating point environment.
Haifeng Li, Leiyan Guo (2025)
Applications of Mathematics
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We investigate the recovery of -sparse signals using the - minimization model with prior support set information. The prior support set information, which is believed to contain the indices of nonzero signal elements, significantly enhances the performance of compressive recovery by improving accuracy, efficiency, reducing complexity, expanding applicability, and enhancing robustness. We assume -sparse signals with the prior support which is composed of true indices and wrong...
Ján Plavka (2016)
Kybernetika
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A vector is said to be an eigenvector of a square max-min matrix if . An eigenvector of is called the greatest -eigenvector of if and for each eigenvector . A max-min matrix is called strongly -robust if the orbit reaches the greatest -eigenvector with any starting vector of . We suggest an algorithm for computing the greatest -eigenvector of and study the strong -robustness. The necessary and sufficient conditions for strong -robustness are introduced...