Title :
A normalized block LMS algorithm for frequency-domain Volterra filters
Author_Institution :
Dept. of inf. & Telecommun. Eng., Soongsil Univ., Seoul, South Korea
Abstract :
The objective of the paper is to introduce a new adaptive filtering algorithm for estimating frequency-domain second-order Volterra filter coefficients. The approach rests upon the normalized LMS (NLMS) algorithm and the frequency-domain block LMS algorithm. The utilization of the normalized LMS algorithm facilitates choice of a proper step size, with which the adaptive frequency domain Volterra filter is guaranteed to be convergent in the mean-squared sense, and improves convergence rate. The frequency-domain block LMS algorithm estimates frequency-domain second-order Volterra filter coefficients which correspond to the DFT of the time-domain Volterra filter coefficients
Keywords :
adaptive filters; convergence of numerical methods; estimation theory; frequency-domain analysis; least mean squares methods; nonlinear filters; adaptive filtering algorithm; block LMS algorithm; convergence rate; frequency-domain Volterra filters; normalized block LMS algorithm; second-order Volterra filter coefficients; step size; Adaptive filters; Convergence; Digital filters; Frequency domain analysis; Frequency estimation; Information filtering; Information filters; Least squares approximation; Nonlinear filters; Time domain analysis;
Conference_Titel :
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Banff, Alta.
Print_ISBN :
0-8186-8005-9
DOI :
10.1109/HOST.1997.613506
