Abstract
This paper proposes a cascaded LMS-RLS prediction filter for improved performance in non-stationary environments. In this proposed filter, an LMS filter with varying step-size is used as the initial filter for achieving faster convergence rate and then a RLS filter for obtaining improved convergence. Theoretical analysis shows that the proposed technique improves the behavior of the adaptive filter in steady state. Computer simulations using MATLAB SIMULINK validate its performance as the error is found to be significantly less compared to the error rates of individual LMS and RLS filters.
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.
