Abstract
The performance of the frequency-domain block least-mean-square (FBLMS) adaptive digital filters, whose filter weights are updated efficiently using the fast Fourier transform, is investigated. In particular, the convergence of the unconstrained FBLMS algorithm with reduced complexity, which is obtained by removing the constraint that has been known to be required in adjusting the frequency-domain weights based on overlap-save sectioning, is analyzed. The performance of the self-orthogonalizing FBLMS algorithm with improved convergence speed, in which different convergence factors normalized by frequency-domain power estimates are used for different frequency components of the weights, is also studied. >
Sign-in/Register to access full text options 
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.
