Nonlinear RLS algorithm for amplitude estimation in class A noise

Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal

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Original languageEnglish
Pages (from-to)81-86
Journal / PublicationIEE Proceedings: Communications
Volume147
Issue number2
Publication statusPublished - 2000

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DOI

DOI
Check@CityULib
Link to Scopus https://www.scopus.com/record/display.uri?eid=2-s2.0-0033876477&origin=recordpage
Permanent Link https://scholars.cityu.edu.hk/en/publications/publication(68945330-44e8-4016-bc75-b4e47affc939).html

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.

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100
Recursive Engineering
100
Least Square Engineering
100
recursive least squ... Computer Science
100
recursive least squ... Computer Science
100
Amplitude Estimatio... Computer Science
33
Good Performance Computer Science
33
Gaussian Input Computer Science
33
Cramer-Rao Bound Computer Science
33
Gaussian Input Sign... Computer Science
16
Simulation Result Engineering
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Citation Format(s)

[ RIS ] [ BibTeX ]
Nonlinear RLS algorithm for amplitude estimation in class A noise. / Weng, J. F.; Leung, S. H.
In: IEE Proceedings: Communications, Vol. 147, No. 2, 2000, p. 81-86.

Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal