On the modeling of linear system input stochastic processes with given accuracy and reliability

On the modeling of linear system input stochastic processes with given accuracy and reliability AbstractThe paper is devoted to the model construction for input stochastic processes of a time-invariant linear system with a real-valued square-integrable impulse response function.The processes are considered as Gaussian stochastic processes with discrete spectrum.The response on the system is supposed to be an output process.We obtain the conditions under which the constructed model approximates a Gaussian stochastic process with given accuracy and reliability in the Banach space C⁢([0,1]){C([0,1])}, taking into account the response of the system. For this purpose, the methods and properties of square-Gaussian processes are used. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Monte Carlo Methods and Applications de Gruyter

On the modeling of linear system input stochastic processes with given accuracy and reliability

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Publisher
de Gruyter
Copyright
© 2018 Walter de Gruyter GmbH, Berlin/Boston
ISSN
1569-3961
eISSN
1569-3961
D.O.I.
10.1515/mcma-2018-0011
Publisher site
See Article on Publisher Site

Abstract

AbstractThe paper is devoted to the model construction for input stochastic processes of a time-invariant linear system with a real-valued square-integrable impulse response function.The processes are considered as Gaussian stochastic processes with discrete spectrum.The response on the system is supposed to be an output process.We obtain the conditions under which the constructed model approximates a Gaussian stochastic process with given accuracy and reliability in the Banach space C⁢([0,1]){C([0,1])}, taking into account the response of the system. For this purpose, the methods and properties of square-Gaussian processes are used.

Journal

Monte Carlo Methods and Applicationsde Gruyter

Published: Jun 1, 2018

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