Development of Information System Optimization Methods Based on Wavelet Canonical Expansions and Wavelet Neural Network Technologies

DOI: https://doi.org/10.25559/SITITO.021.202501.46-55

Abstract

Canonical expansion (CE) of stochastic processes (StP) are widely used in applied mathematics, informatics and control. Based on wavelet computing technologies, the authors developed the theory of wavelet canonical decompositions (WCDE), as well as the theory of canonical decompositions based on a wavelet neural network (WNNN). In the report, after a brief review of the development of the theory of canonical expansions, wavelet-canonical expansions and the theory of canonical expansions based on a wavelet neural network, a method for synthesizing an optimal information system based on the energy criterion (EC) is considered. Problem statement is given for V.S. Pugachev IS and WCDE. WCDE is constructed of CE of input StP. Equations for EC-optimal operator are presented. Formulae for mathematical expectation and variance of EC-optimal output StP estimate are outlined. Illustrate example confirms effective of suggested method in comparison with other two known methods.

Author Biographies

Igor Nikolaevich Sinitsyn, Federal Research Center Computer Science and Control of the Russian Academy of Sciences

Chief Researcher of Department No. 61 "Stochastic Problems of Informatics" of Division 6 "Stochastic and Intelligent Methods and Tools for Modeling and Building Systems with Intensive Use of Data", Dr. Sci. (Tech.), Professor

Vladimir Igorevich Sinitsyn, Federal Research Center Computer Science and Control of the Russian Academy of Sciences

Chief Researcher, Head of Division 6 "Stochastic and Intelligent Methods and Tools for Modeling and Building Systems with Intensive Use of Data", Dr. Sci. (Phys.-Math.)

Eduard Rudolfovich Korepanov, Federal Research Center Computer Science and Control of the Russian Academy of Sciences

Leading Researcher, Head of Department No. 61 "Stochastic Problems of Informatics" of Division 6 "Stochastic and Intelligent Methods and Tools for Modeling and Building Systems with Intensive Use of Data", Cand. Sci. (Eng.), Professor

Tatyana Dmitrievna Konashenkova, Federal Research Center Computer Science and Control of the Russian Academy of Sciences

Research Fellow of Department No. 61 "Stochastic Problems of Informatics" of Division 6 "Stochastic and Intelligent Methods and Tools for Modeling and Building Systems with Intensive Use of Data", Cand. Sci. (Phys.-Math.)

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Published
2025-04-28
How to Cite
SINITSYN, Igor Nikolaevich et al. Development of Information System Optimization Methods Based on Wavelet Canonical Expansions and Wavelet Neural Network Technologies. Modern Information Technologies and IT-Education, [S.l.], v. 21, n. 1, p. 46-55, apr. 2025. ISSN 2411-1473. Available at: <http://sitito.cs.msu.ru/index.php/SITITO/article/view/1183>. Date accessed: 23 aug. 2025. doi: https://doi.org/10.25559/SITITO.021.202501.46-55.
Citation Formats
Issue
Vol 21 No 1 (2025): Modern Information Technologies and IT-education
Section
Applied optimization problems
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