2024, issue 1, p. 64-74
Received 04.03.2024; Revised 11.03.2024; Accepted 19.03.2024
Published 29.03.2024; First Online 31.03.2024
https://doi.org/10.34229/2707-451X.24.1.5
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Optimal with Respect to Accuracy Recovery of Some Classes Functions by Fourier Series
V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine, Kyiv
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Introduction. Function approximation (approximation or restoration) is widely used in data analysis, model building, and forecasting. The goal of function approximation is to find the function that best approximates the original function. This can be useful when the original function is too complex to analyze or when a model needs to be simplified for more efficient computation or interpretation. Function approximation is an important tool in science, engineering, economics, and other fields where data analysis and modeling are required. It allows you to simplify complex functions, identify patterns in the behavior of the object of study, and predict the value of a function beyond the available data.
The purpose of the paper is consider the problems of approximation of a function, which on some interval is given by its values in some set of nodal points and belongs to some class of functions by trigonometric Fourier series with a given accuracy and at fulfillment of given constraints on its execution time. The main attention is paid to obtaining estimates of computational complexity (implementation time) and solving the problem of function approximation by Fourier series with a given or maximum possible accuracy using efficient algorithms for solving optimization problems.
Results. The general formulation of the problem of approximation of functions by Fourier series in accordance with the technology of solving problems of computational and applied mathematics with specified values of quality characteristics is presented. Estimates of the error of the proposed approximation algorithms using for the computation of Fourier coefficients the optimal in accuracy and close to them quadrature formulas for the computation of integrals from rapidly oscillating functions of the classes of Helder and Lipschitz with given fixed values in the nodes of a fixed grid are given. The corresponding quadrature formulas and constructive estimates of the error of the method of approximation of functions of the specified classes are given. Estimates of computational complexity of the given algorithms are obtained, which allow us to set real constraints on the time of algorithm implementation with a given or maximum possible accuracy.
Conclusions. A comprehensive analysis of the quality of the considered algorithms for the approximation of functions by Fourier series using the accuracy-optimal (or close to them) quadrature formulas for the computation of Fourier coefficients for the computation of integrals from rapidly oscillating functions is presented. The estimates of their main characteristics – accuracy and computational complexity – are obtained.
Keywords: function approximation, Fourier series, Fourier series coefficients, approximation error, computational complexity.
Cite as: Kolomys O. Optimal with Respect to Accuracy Recovery of Some Classes Functions by Fourier Series. Cybernetics and Computer Technologies. 2024. 1. P. 64–74. (in Ukrainian) https://doi.org/10.34229/2707-451X.24.1.5
References
1. Zadiraka V.K., Melnikova S.S. Digital signal processing. Kiev: Scientific Opinion, 1993. 294 p. (in Russian)
2. Sergienko I.V., Zadiraka V.K., Lytvyn O.M., Melnikova S.S., Nechuyviter O.P. Optimal algorithms for calculating integrals from fast-oscillating functions and their application. Vol. 1 Algorithms. Kiev: Scientific Opinion, 2011. 447 p. Vol. 2 Application. Kiev: Scientific Opinion, 2011. 346 p. (in Ukrainian)
3. Fichtenholtz G.M. Course of differential and integral calculus. T. 3. M.: Fizmatlit, 2001. 662 p. (in Russian)
4. Stepanets A.I. Methods of Approximation Theory. VSP: Leiden, Boston, 2005. 919 p. https://doi.org/10.1515/9783110195286
5. Zadiraka V.K., Babych M.D., Berezovsky A.I. etc. T-efficient algorithms for approximate solution of problems of computational and applied mathematics. Ternopil: Zbruch, 2003. 261 p. (in Ukrainian)
6. Кolomys O.M. Effective by precision algorithms for approximation of functions from the Gelder class by Fourier’s series. Physico-mathematical modelling and informational technologies. 2021. No. 32. P. 159–164. https://doi.org/10.15407/fmmit2021.32.159 (in Ukrainian)
7. Кolomys O.M., Lutz L.V. Effective by precision algorithms for approximation of functions from the Lipschitz class by Fourier’s series. Physico-mathematical modelling and informational technologies. 2023. No. 36. P. 111–115. https://doi.org/10.15407/10.15407/fmmit2023.36.111 (in Ukrainian)
ISSN 2707-451X (Online)
ISSN 2707-4501 (Print)
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