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Titolo:
A confluence matrix condition for exponential error convergence in overparametrized adaptive systems
Autore:
Bayard, DS;
Indirizzi:
CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA CALTECH Pasadena CA USA 91109 LTECH, Jet Prop Lab, Pasadena, CA 91109 USA
Titolo Testata:
IEEE TRANSACTIONS ON SIGNAL PROCESSING
fascicolo: 6, volume: 48, anno: 2000,
pagine: 1656 - 1666
SICI:
1053-587X(200006)48:6<1656:ACMCFE>2.0.ZU;2-S
Fonte:
ISI
Lingua:
ENG
Soggetto:
FEEDFORWARD SYSTEMS; LMS ALGORITHM; INTERFERENCE; CANCELLATION; REGRESSORS; EXCITATION; STABILITY; SCHEMES; NOISE;
Keywords:
adaptive signal processing; asymptotic stability; feedforward systems; least mean square methods; persistent excitation;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
--discip_EC--
Citazioni:
23
Recensione:
Indirizzi per estratti:
Indirizzo: Bayard, DS CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USA CALTECH 4800 Oak Grove Dr Pasadena CA USA 91109 a, CA 91109 USA
Citazione:
D.S. Bayard, "A confluence matrix condition for exponential error convergence in overparametrized adaptive systems", IEEE SIGNAL, 48(6), 2000, pp. 1656-1666

Abstract

Many practical adaptive feedforward systems are overparametrized and, for this reason, will not satisfy persistent excitation (PE) conditions. For these systems, a weaker PE condition is proposed under which it is shown thatthe while parameters may not converge, the cancellation error (the error between the desired and estimated outputs) still converges exponentially. Bounds are given on the exponential rate of convergence useful for understanding the various tradeoffs and for systematic optimization and design purposes, The convergence rate is determined by properties of the confluence matrix (defined herein) that plays a role similar to that played by the autocorrelation matrix for fully PE systems. As a case study, the structure of theconfluence matrix is examined in detail for adaptive systems with a tap delay line (TDL) regressor and sinusoid excitation.

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Documento generato il 01/06/20 alle ore 02:32:52