Dynamical systems identification from time-series data: A hankel matrix approach

Authors:
D. Lai;G. Chen
Affiliations:
Program in Biometry, School of Public Health University of Texas at Houston, Houston, TX 77030, U.S.A.;Department of Electrical and Computer Engineering University of Houston, Houston, TX 77204, U.S.A.
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
1996

Citing 3
Cited 1

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Abstract

In this paper, we propose a simple but effective method for dynamical systems identification using time-series data. The method works perfectly well for deterministic dynamical systems and works reasonably well for a general class of stochastic dynamical systems. Both computer simulation studies and theoretical analysis are provided to validate the proposed methods.