Title :
Fast adaptive filtering algorithm based on exponentially weighted least-square errors
Author_Institution :
Div. of Inf. & Comput. Eng., Ajou Univ., Suwon, South Korea
fDate :
10/28/1999 12:00:00 AM
Abstract :
The linearly filtered gradient least mean square algorithm is reformulated using exponentially weighted least-square errors, and a partially filtered gradient LMS algorithm is proposed as a variant. It is shown that the proposed algorithm is superior in terms of convergence and tracking capability compared to the LMS and FGLMS algorithms
Keywords :
adaptive filters; convergence of numerical methods; least mean squares methods; tracking; adaptive filtering algorithm; convergence; exponentially weighted least-square errors; partially filtered gradient LMS; tracking capability;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19991324
