Title :
Learning algorithm for total least-squares adaptive signal processing
Author :
Gao, K. ; Ahmad, M.O. ; Swamy, M.N.S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada
Abstract :
A new adaptive learning algorithm, called the constrained anti-Hebbian algorithm, is presented. This algorithm is optimal in the total least-squares sense, simple to use, and can be applied to on-line adaptive FIR and IIR filtering directly. Simulation results confirm that the proposed algorithm provides significantly better performance over the least mean-squares (LMS) and recursive least-squares (RLS) algorithms.
Keywords :
adaptive systems; filtering and prediction theory; learning systems; least squares approximations; signal processing; FIR filtering; IIR filtering; adaptive learning algorithm; adaptive signal processing; constrained anti-Hebbian algorithm; total least-squares;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19920270
