Abstract
The paper deals with a nonparametric, (statistical) identification model of continuous nonlinear dynamic system, especially with the identification of continuous Hammerstein systems with white noise input applying the dispersional method. It discusses how the Rajbman's cross dispersion function plays an analog role in the identification problem of continuous Hammerstein systems to that played by the cross correlation function in the case of the "active" identification of linear systems. The method introduced can ensure an optimal estimation of the nonlinear static and linear dynamic part of the Hammerstein system according to the mean square error. The paper gives results obtained by computer simulation as well as identification model applications.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
