Problem of reconstructing a disturbance in a linear stochastic equation: The case of incomplete information

Autor:	V. L. Rozenberg
Rok vydání:	2014
Předmět:	Stochastic partial differential equation Stochastic differential equation Continuous-time stochastic process Mathematical optimization Mathematics (miscellaneous) Rate of convergence Covariance matrix Stochastic process Ordinary differential equation Applied mathematics Inverse problem Mathematics
Zdroj:	Proceedings of the Steklov Institute of Mathematics. 287:167-174
ISSN:	1531-8605 0081-5438
DOI:	10.1134/s0081543814090168
Popis:	The problem of reconstructing an unknown deterministic disturbance characterizing the level of random noise in a linear stochastic second-order equation is investigated based on the approach of dynamic inversion theory. The reconstruction is performed with the use of discrete information on a number of realizations of one coordinate of the stochastic process. The problem under consideration is reduced to an inverse problem for a system of ordinary differential equations describing the covariance matrix of the original process. A finite-step solving algorithm based on the method of auxiliary controlled models is suggested. Its convergence rate with respect to the number of measured realizations is estimated.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a1521002f085db9691d4fe6baf9c78d1 https://doi.org/10.1134/s0081543814090168 Zobrazit plný text záznamu Full text from SpringerLink