Bayes Synthesis of Linear Nonstationary Stochastic Systems by Wavelet Canonical Expansions

Igor Sinitsyn, Vladimir Sinitsyn, Eduard Korepanov and Tatyana Konashenkova
Additional contact information
Igor Sinitsyn: Federal Research Center “Computer Science and Control”, Russian Academy of Sciences (FRC CSC RAS), 119333 Moscow, Russia
Vladimir Sinitsyn: Federal Research Center “Computer Science and Control”, Russian Academy of Sciences (FRC CSC RAS), 119333 Moscow, Russia
Eduard Korepanov: Federal Research Center “Computer Science and Control”, Russian Academy of Sciences (FRC CSC RAS), 119333 Moscow, Russia
Tatyana Konashenkova: Federal Research Center “Computer Science and Control”, Russian Academy of Sciences (FRC CSC RAS), 119333 Moscow, Russia

Mathematics, 2022, vol. 10, issue 9, 1-14

Abstract: This article is devoted to analysis and optimization problems of stochastic systems based on wavelet canonical expansions. Basic new results: (i) for general Bayes criteria, a method of synthesized methodological support and a software tool for nonstationary normal (Gaussian) linear observable stochastic systems by Haar wavelet canonical expansions are presented; (ii) a method of synthesis of a linear optimal observable system for criterion of the maximal probability that a signal will not exceed a particular value in absolute magnitude is given. Applications: wavelet model building of essentially nonstationary stochastic processes and parameters calibration.

Keywords: Bayes criterion; Haar wavelets; loss function; mean risk; observable stochastic systems (OStS); stochastic process (StP); wavelet canonical expansion (WLCE) (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/9/1517/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/9/1517/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:9:p:1517-:d:807379

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().