Abstract

AbstractTwo identification algorithms, a least squares and a correlation analysis based, are developed for dual‐rate stochastic systems in which the output sampling period is an integer multiple of the input updating period. The basic idea is to use auxiliary FIR models to predict unmeasurable noise‐free (true) outputs, and then use these and system inputs to identify parameters of underlying fast single‐rate models. The simulation results indicate that the proposed algorithms are effective. Copyright © 2004 John Wiley & Sons, Ltd.

Full Text
Paper version not known

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 call

Disclaimer: 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.