Results 231 to 240 of about 30,959 (260)
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Approximate structural reanalysis based on series expansion
Computer Methods in Applied Mechanics and Engineering, 1981Abstract In most optimal design procedures the analysis of the structure must be repeated many times. This operation, which involves much computational effort, is one of the main difficulties in applying optimization methods to large systems. This study deals with approximate reanalysis methods based on series expansion.
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A Comparison of “Best” Polynomial Approximations with Truncated Chebyshev Series Expansions
Journal of the Society for Industrial and Applied Mathematics Series B Numerical Analysis, 1964Introduction. In the numerical solution of mathematical problems it is common to represent a function of a real variable by the leading terms of its infinite Chebyshev series expansion. The purpose of this paper is to compare the accuracy of such a polynomial approximation with that of the "best" polynomial approximation of the same degree (the "best ...
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A recursive method for the approximate expansion of functions in a series of polynomials
Computer Physics Communications, 1972Abstract In this paper we describe a recursive procedure for the approximate evaluation of the coefficients of expansion of a function y(x) in a system of polynomials λ = [λk(x)], k∈N. Numerical examples and the computational procedure are also discussed.
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Publicationes Mathematicae Debrecen, 2022
Wiener-Itô integrals are used to give the Wiener series expansion for a quadratic of the observation model which is a special case of the state dependent model. Wiener kernels for the product of two nonlinear processes are determined. Some explicit formulae for the product of multiple Wiener-Itô integrals are received.
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Wiener-Itô integrals are used to give the Wiener series expansion for a quadratic of the observation model which is a special case of the state dependent model. Wiener kernels for the product of two nonlinear processes are determined. Some explicit formulae for the product of multiple Wiener-Itô integrals are received.
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On the Estimate of the K-Factor: An Effective Approximation Based on Taylor Series Expansion
IEEE Transactions on Electromagnetic Compatibility, 2020In this letter, an approximate estimator of the K -factor ( K ) for wireless channels is obtained. It is based on the use of a second-order Taylor expansion of the analytical expression of the K maximum likelihood estimator (MLE) of available in the literature for wireless channels emulated in reverberation chamber.
Gifuni, Angelo, Perna, Stefano
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Linear Approximations of Nonlinear Relationships by the Taylor's Series Expansion Revisited
1972This paper examines the magnitude of error associated with linear approximations of nonlinear variables based on Taylor's Series. Little attention has been given to the error term in previous empirical studies. This paper presents the mathematical technique for the single-variable and twovariable cases.
Womack, Abner W., Matthews, Jimmy L.
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Series Expansion Approximants for Singular Functions of Many Variables
1977A novel method of approximating functions of two or more variables given a finite number of coefficients of their power series expansions is explained. The method — partial differential approximation — is effective in representing the characteristic singularities to be expected in functions of two or more variables (typically those arising in ...
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APPROXIMATING THE DENSITY OF THE TIME TO RUIN VIA FOURIER-COSINE SERIES EXPANSION
ASTIN Bulletin, 2016AbstractIn this paper, the density of the time to ruin is studied in the context of the classical compound Poisson risk model. Both one-dimensional and two-dimensional Fourier-cosine series expansions are used to approximate the density of the time to ruin, and the approximation errors are also obtained.
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From high oscillation to rapid approximation II: expansions in Birkhoff series
IMA Journal of Numerical Analysis, 2011We consider the use of eigenfunctions of polyharmonic operators, equipped with homogeneous Neumann boundary conditions, to approximate nonperiodic functions in compact intervals. Such expansions feature a number of advantages in comparison with classical Fourier series, including uniform convergence and more rapid decay of expansion coefficients ...
B. Adcock, A. Iserles, S. P. Norsett
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Power series expansion neural network
Journal of Computational Science, 2022Juncai He, Wenrui Hao
exaly