Title :
A variable leaky LMS adaptive algorithm
Author :
Kamenetsky, Max ; Widrow, Bernard
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., CA, USA
Abstract :
The LMS algorithm has found wide application in many areas of adaptive signal processing and control. We introduce a variable leaky LMS algorithm, designed to overcome the slow convergence of standard LMS in cases of high input eigenvalue spread. The algorithm uses a greedy punish/reward heuristic together with a quantized leak adjustment function to vary the leak. Simulation results confirm that the new algorithm can significantly outperform standard LMS when the input eigenvalue spread is high.
Keywords :
adaptive control; adaptive signal processing; eigenvalues and eigenfunctions; least mean squares methods; adaptive control; adaptive signal processing; eigenvalue spread; variable leaky LMS algorithm; Adaptive algorithm; Adaptive signal processing; Cost function; Eigenvalues and eigenfunctions; Iterative algorithms; Least squares approximation; Process control; Random processes; Signal processing algorithms; Vectors;
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on
Print_ISBN :
0-7803-8622-1
DOI :
10.1109/ACSSC.2004.1399103
