Title :
Wavelet transform domain LMS algorithm
Author :
Hosur, Srinath ; Tewfik, Ahmed H.
Author_Institution :
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
Abstract :
A novel normalized wavelet domain least-mean-square (LMS) algorithm is described. The faster convergence rate of this algorithm as compared with time-domain LMS is established. The wavelet domain LMS algorithm requires only real arithmetic. In its most basic form it has a computational complexity that is higher than that of the traditional LMS technique by a factor of cN, where N is the length of the transformed vector (or sliding analysis window) and c is the length of the analysis wavelet. Other preconditioning strategies that yield a faster convergence rate for a given fixed excess mean squared error are discussed. The authors also describe low-complexity implementations of the wavelet domain LMS algorithm. These implementations exploit the structure of the wavelet transform of the underlying stochastic process.<>
Keywords :
adaptive filters; computational complexity; convergence of numerical methods; digital arithmetic; filtering and prediction theory; least squares approximations; wavelet transforms; LMS algorithm; adaptive filtering; computational complexity; convergence rate; preconditioning strategies; real arithmetic; stochastic process; wavelet domain;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on
Conference_Location :
Minneapolis, MN, USA
Print_ISBN :
0-7803-7402-9
DOI :
10.1109/ICASSP.1993.319546
