Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
Subspace-based Identification for Continuous-Time Stochastic Systems via Distribution-Theoretic Approach
Akira OHSUMIKentaro KAMEYAMAKen-Ichi YAMAGUCHI
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2000 Volume 13 Issue 7 Pages 338-345

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Abstract

This paper presents a novel approach for system identification of continuous-time stochastic state space models from random input-output continuous data. The approach is based on the introduction of the random distribution theory in describing the (higher) time derivatives of stochastic processes, and the input-output algebraic relationship is derived which is treated in the time-domain. The efficacy of the approach proposed is examined by comparing with other approaches employing the filters.

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