Abstract

SUMMARYThe paper analyzes the transient and steady‐state performances of a least mean square algorithm in the rarely‐studied situation of a time‐varying input power. A scenario of periodic pulsed variation of the input power is considered. The analysis is carried out in the context of tracking a Markov plant with a white Gaussian input. It is shown that the mean square deviation (MSD) converges to a periodic sequence having the same period as that of the variation of the input power. Expressions are derived for the convergence time and the steady‐state peak MSD. Surprisingly, it is found that neither the transient performance nor the steady‐state performance degrades with rapid variation of the input power. On the other hand, slow input power variation causes degradation in both the transient and steady‐state performances for given amplitude of variation of the input power. In the case of a time‐invariant plant, neither rapid nor slow variation of the input power causes degradation in the steady‐state performance. On the other hand, there is degradation in the transient performance for slow variation of the input power. Copyright © 2012 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.