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Proceedings of the National Academy of Sciences of Belarus. Physics and Mathematics Series

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Fourier series for the multidimensional-matrix functions of the vector variable

https://doi.org/10.29235/1561-2430-2024-60-1-15-28

Abstract

In the article, the theory of the Fourier series on the orthogonal multidimensional-matrix (mdm) polynomials is developed. The known results from the theory of the orthogonal polynomials of the vector variable and the Fourier series are given and the new results are presented. In particular, the known results of the Fourier series theory are extended to the case of the mdm functions, what allows us to solve more general approximation problems. The general case of the approximation of the mdm function of the vector argument by the Fourier series on the orthogonal mdm polynomials is realized programmatically as the program function and its efficiency is confirmed. The analytical expressions for the coefficients of the second degree orthogonal polynomials and Fourier series for possible analytical studies are obtained.

About the Author

V. S. Mukha
Belarusian State University of Informatics and Radioelectronics
Belarus

Vladimir S. Mukha – Dr. Sc. (Engineering), Professor, Professor of the Department of Information Technologies of Automated Systems

6, P. Brovka Str., 220013, Minsk



References

1. Hermite M. Sur un nouveau doveloppement en serie des fonctions. Comptes Rendus hebdomadaires des seances de l’Academie des Sciences, 1864, vol. 58, pp. 93–100, 266–273.

2. Appel P., Kampe de Feriet. Fonctions Hypergeometriques et Hyperspheriques. Polynomes D’Hermite. Paris, 1926. 390 p.

3. Sirazhdinov S. H. To the theory of the multivariate Hermite polynomials. Proceedings of the Institute of Mathematics and Mechanics of the Akademy of Sciences of the UzSSR, 1949, iss. 5, pp. 70–95 (in Russian).

4. Mysovskikh I. P. Interpolation Cubature Formulae. Moscow, Nauka Publ., 1981. 336 p. (in Russian).

5. Suetin P. K. Orthogonal Polynomials in Two Variables. Moscow, Nauka Publ., 1988. 384 p. (in Russian).

6. Dunkl C. F., Yuan Xu. Orthogonal Polynomials of Several Variables. 2nd ed. Cambridge University Press, 2014. 450 p. https://doi.org/10.1017/cbo9781107786134

7. Sokolov N. P. Spatial Matrices and their Application. Moscow, Fizmatgiz Publ., 1960. 300 p. (in Russian).

8. Sokolov N. P. Introduction to the Theory of Multidimensional Matrices. Kiev, Naukova dumka Publ., 1972. 176 p. (in Russian).

9. Mukha V. S. Modeling of the Multidimensional Systems and Processes. Multidimensional-Matrix Approach. Minsk, BSUIR, 1998. 40 p. (in Russian).

10. Mukha V. S. Analysis of Multidimensional Data. Minsk, Technoprint Publ., 2004. 368 p. (in Russian).

11. Mukha V. S. Mathematical models of the multidimensional data. Doklady BSUIR, 2014, no. 2 (80), pp. 143–158 (in Russian).

12. Smilde A., Bro R., Geladi P. Multi-Way Analysis with Applications in the Chemical Sciences. John Wiley & Sons, Inc., 2004. 396 p. https://doi.org/10.1002/0470012110

13. Kroonenberg P. M. Applied Multiway Data Analysis. John Wiley & Sons, Inc., 2008. 579 p. https://doi.org/10.1002/9780470238004

14. Ashu M. G. Solo. Multidimensional matrix mathematics. Part 1–6. Proceedings of the World Congress on Engineering. Vol. III. (WCE 2010, June 30 – July 2, 2010, London, U. K.). [S. l.], 2010, pp. 1824–1850.

15. Mukha V. S. Multidimensional-matrix approach to the theory of the orthogonal systems of the polynomials of the vector variable. Vestsі Natsyyanalʼnai akademіі navuk Belarusі. Seryya fіzіka-matematychnykh navuk = Proceedings of the National Academy of Sciences of Belarus. Physics and Mathematics series, 2001, no. 2, pp. 64–68 (in Russian).

16. Mukha V. S. Bayesian multidimensional-matrix polynomial empirical regression. Control and Cybernetics, 2020, vol. 49, no. 3, pp. 291–315.

17. Mukha V. S. Systems of the polynomials orthogonal with discrete weight. Vestsі Natsyyanalʼnai akademіі navuk Belarusі. Seryya fіzіka-matematychnykh navuk = Proceedings of the National Academy of Sciences of Belarus. Physics and Mathematics series, 2004, no. 1, pp. 69–73 (in Russian).

18. Mukha V. S. The best polynomial multidimensional-matrix regression. Cybernetics and System Analysis, 2007, vol. 43, no. 3, pp. 427–432.


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ISSN 1561-2430 (Print)
ISSN 2524-2415 (Online)