Abstract:
The empirical distributions of functional including moments, defining over the ensemble of trajectories of non-stationary time-series, are investigated. The distribution of time-series is determined by some empirical kinetic equation of diffusion type. This approach enables to solve several problems in the area of stochastic control, connecting with self-organization effects.
Keywords:
non-stationary time series, ensemble of trajectories, mathematical modeling, functional distributions.
Citation:
Yu. N. Orlov, S. L. Fedorov, “Functional distributions modeling over trajectories ensemble of non-stationary time series”, Keldysh Institute preprints, 2016, 101, 14 pp.
\Bibitem{OrlFed16}
\by Yu.~N.~Orlov, S.~L.~Fedorov
\paper Functional distributions modeling over trajectories ensemble of non-stationary time series
\jour Keldysh Institute preprints
\yr 2016
\papernumber 101
\totalpages 14
\mathnet{http://mi.mathnet.ru/ipmp2175}
\crossref{https://doi.org/10.20948/prepr-2016-101}
Linking options:
https://www.mathnet.ru/eng/ipmp2175
https://www.mathnet.ru/eng/ipmp/y2016/p101
This publication is cited in the following 2 articles:
A. A. Kislitsyn, A. B. Kozlova, M. B. Korsakova, E. L. Masherov, Yu. N. Orlov, “Statsionarnaya tochka urovnya znachimosti dlya nestatsionarnykh funktsii raspredeleniya”, Preprinty IPM im. M. V. Keldysha, 2018, 113, 20 pp.
A. A. Kislitsyn, A. B. Kozlova, E. L. Masherov, Yu. N. Orlov, “Numerical algorithm for self-consistent stationary level for multidimensional non-stationary time-series”, Preprinty IPM im. M. V. Keldysha, 2017, 124, 14 pp.
Citation in format AMSBIB
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