TY - JOUR
T1 - Nonlinear RLS algorithm for amplitude estimation in class A noise
AU - Weng, J. F.
AU - Leung, S. H.
PY - 2000
Y1 - 2000
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0033876477&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0033876477&origin=recordpage
U2 - 10.1049/ip-com:20000182
DO - 10.1049/ip-com:20000182
M3 - RGC 22 - Publication in policy or professional journal
SN - 1350-2425
VL - 147
SP - 81
EP - 86
JO - IEE Proceedings: Communications
JF - IEE Proceedings: Communications
IS - 2
ER -