Bayes Synthesis of Linear Nonstationary Stochastic Systems by Wavelet Canonical Expansions

Bayes Synthesis of Linear Nonstationary Stochastic Systems by Wavelet Canonical Expansions

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 stoch...

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Bibliographic Details
Main Authors: Igor Sinitsyn, Vladimir Sinitsyn, Eduard Korepanov, Tatyana Konashenkova
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Mathematics
Subjects:
Bayes criterion
Haar wavelets
loss function
mean risk
observable stochastic systems (OStS)
stochastic process (StP)
Online Access:https://www.mdpi.com/2227-7390/10/9/1517

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https://www.mdpi.com/2227-7390/10/9/1517

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