Title :
Nonlinear RLS algorithm for amplitude estimation in class A noise
Author :
Weng, J.F. ; Leung, S.H.
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong
fDate :
4/1/2000 12:00:00 AM
Abstract :
An adaptive nonlinear recursive least square (RLS) algorithm for amplitude estimation in class A noise is presented. For Gaussian input signal and class A noise, its mean and mean-square behaviours are studied. It is shown that the linear RLS and nonlinear RLS algorithm with the clipper function are stable in the mean and mean square. For non-Gaussian input, amplitude estimation in CDMA communication is presented. Simulation results show that the nonlinear RLS can provide good performance close to the Cramer-Rao bound and outperform the nonlinear LMS and the conventional RLS in impulse noise
Keywords :
adaptive estimation; amplitude estimation; code division multiple access; convergence of numerical methods; filtering theory; impulse noise; least squares approximations; nonlinear estimation; recursive estimation; CDMA communication; Cramer-Rao bound; Gaussian input signal; RLS algorithm; adaptive nonlinear recursive least square algorithm; amplitude estimation; class A noise; clipper function; impulse noise; mean behaviour; mean-square behaviour; non-Gaussian input signal; simulation results;
Journal_Title :
Communications, IEE Proceedings-
DOI :
10.1049/ip-com:20000182
