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Titolo:
Detection guided NLMS estimation of sparsely parametrized channels
Autore:
Homer, J;
Indirizzi:
Univ Queensland, Cooperat Res Ctr Sensor Signal & Informat Proc, Sch Comp Sci & Elect Engn, Brisbane, Qld 4072, Australia Univ Queensland Brisbane Qld Australia 4072 Brisbane, Qld 4072, Australia
Titolo Testata:
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING
fascicolo: 12, volume: 47, anno: 2000,
pagine: 1437 - 1442
SICI:
1057-7130(200012)47:12<1437:DGNEOS>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
LMS;
Keywords:
adaptive filters; least mean square methods; least squares methods; echo suppression; transient analysis;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
--discip_EC--
Citazioni:
15
Recensione:
Indirizzi per estratti:
Indirizzo: Homer, J Univ Queensland, Cooperat Res Ctr Sensor Signal & Informat Proc, Sch Comp Sci & Elect Engn, Brisbane, Qld 4072, Australia Univ Queensland Brisbane Qld Australia 4072 Qld 4072, Australia
Citazione:
J. Homer, "Detection guided NLMS estimation of sparsely parametrized channels", IEEE CIR-II, 47(12), 2000, pp. 1437-1442

Abstract

We consider the normalized least mean square (NLMS) estimation of a channel, which may be well approximated by a finite impulse response model with sparsely separated active or nonzero taps. Previously reported analyses imply that the convergence rate of the NLMS estimator should be greatly enhanced if only the active taps are estimated, We propose an NLMS estimator, which incorporates a least squares based active tap detection method. Simulations demonstrate that the NLMS estimator has significantly faster convergencethan the standard NLMS estimator for colored as well as white input signals, Furthermore, for sparse channels, this improved convergence speed is accompanied by a lower computational cost.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 09/04/20 alle ore 07:26:06