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Nonlinear RLS algorithm for amplitude estimation in class A noise

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2 Author(s)
Weng, J.F. ; Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong ; Leung, S.H.

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

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Communications, IEE Proceedings-  (Volume:147 ,  Issue: 2 )