Estimating stationary characteristic functions of stochastic systems via semidefinite programming

Khem Raj Ghusinga, Andrew Lamperski, Abhyudai Singhl

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper proposes a methodology to estimate characteristic functions of stochastic differential equations that are defined over polynomials. For such systems, the time evolution of the characteristic function is governed by a partial differential equation; consequently, the stationary characteristic function can be obtained by solving an ordinary differential equation (ODE). However, except for a few special cases, the solution to the ODE consists of unknown coefficients. These coefficients are closely related with the stationary moments of the process, which could be estimated by utilizing the fact that the characteristic function is positive definite. The method is illustrated via examples.

Original languageEnglish (US)
Title of host publication2018 European Control Conference, ECC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2720-2725
Number of pages6
ISBN (Electronic)9783952426982
DOIs
StatePublished - Nov 27 2018
Event16th European Control Conference, ECC 2018 - Limassol, Cyprus
Duration: Jun 12 2018Jun 15 2018

Publication series

Name2018 European Control Conference, ECC 2018

Other

Other16th European Control Conference, ECC 2018
CountryCyprus
CityLimassol
Period6/12/186/15/18

Bibliographical note

Funding Information:
ACKNOWLEDGMENT AS is supported by the National Science Foundation Grant ECCS-1711548.

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