Informatics and Applications
2015, Volume 9, Issue 1, pp 70-75
STABLE LINEAR CONDITIONALLY OPTIMAL FILTERS AND EXTRAPOLATORS FOR STOCHASTIC SYSTEMS WITH MULTIPLICATIVE NOISES
- I.N. Sinitsyn
- E.R. Korepanov
Abstract
The applied theory of analytical synthesis of linear conditionally optimal filters and extrapolators in
linear differential stochastic systems with white multiplicative non-Gaussian noises is presented. Efficient criteria
of unique asymptotic stability of conditionally optimal filters and extrapolators are formulated in terms of special
positive definite integral forms and unique boundedness of controllability and observability matrices. White noises
are assumed to be derivatives of additive and multiplicative non-Gausisan arbitrary stochastic processes with
independent increments. An illustrative example is given. Some generalizations are discussed.
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[+] About this article
Title
STABLE LINEAR CONDITIONALLY OPTIMAL FILTERS AND EXTRAPOLATORS FOR STOCHASTIC SYSTEMS WITH MULTIPLICATIVE NOISES
Journal
Informatics and Applications
2015, Volume 9, Issue 1, pp 70-75
Cover Date
2014-10-30
DOI
10.14357/19922264150106
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
accuracy and unique asymptotic stability of filters; differential stochastic systems; linear conditionally
optimal filters and extrapolators; multiplicative white noises; Riccati equation
Authors
I.N. Sinitsyn  and E.R. Korepanov
Author Affiliations
Institute of Informatics Problems, Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian
Federation
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