Title :
Variable weight mixed-norm LMS-LMF adaptive algorithm
Author :
Aboulnasr, Tyseer ; Zerguine, Azzedine
Author_Institution :
Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont., Canada
Abstract :
In this paper, we propose a new mixed norm LMS-LMF adaptive algorithm. The algorithm minimizes an objective function defined as a weighted sum of the least mean fourth (LMF) and least mean square (LMS) cost functions. The weighting factor is time varying and adapts itself so as to emphasize one cost function over the other based on proximity to the optimum. Improved convergence is illustrated by examples. Bounds on the step size to ensure mean convergence are also derived.
Keywords :
adaptive filters; adaptive signal processing; convergence of numerical methods; filtering theory; least mean squares methods; minimisation; time-varying filters; LMF cost function; LMS cost function; LMS-LMF adaptive algorithm; adaptive filter; convergence; least mean fourth algorithm; least mean square algorithm; objective function minimisation; step size bounds; time varying mixed-norm algorithm; weighting factor; Adaptive algorithm; Adaptive filters; Convergence; Cost function; Equations; Filtering algorithms; Gaussian noise; Information technology; Least squares approximation; Physics;
Conference_Titel :
Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on
Print_ISBN :
0-7803-5700-0
DOI :
10.1109/ACSSC.1999.832437
