On-line identification of nonlinear systems using adaptive matching pursuit

Armin Shmilovici; Oded Maimon

On-line identification of nonlinear systems using adaptive matching pursuit

Armin Shmilovici^*
, Oded Maimon

^*Corresponding author for this work

Boston University

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

A reduced complexity algorithm, which is an adaptive version of the Matching Pursuit algorithm, is proposed for the identification of nonlinear systems. The algorithm is demonstrated on various nonlinear systems presented in the literature. The results are favorable compared to other nonlinear identification methods (e.g. Neural Nets). It is demonstrated that the algorithm could be used for the design of adaptive controllers.

Original language	English
Pages	499-502
Number of pages	4
State	Published - 1996
Externally published	Yes
Event	Proceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel - Jerusalem, Isr Duration: 5 Nov 1996 → 6 Nov 1996

Conference

Conference	Proceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel
City	Jerusalem, Isr
Period	5/11/96 → 6/11/96

Cite this

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title = "On-line identification of nonlinear systems using adaptive matching pursuit",

abstract = "A reduced complexity algorithm, which is an adaptive version of the Matching Pursuit algorithm, is proposed for the identification of nonlinear systems. The algorithm is demonstrated on various nonlinear systems presented in the literature. The results are favorable compared to other nonlinear identification methods (e.g. Neural Nets). It is demonstrated that the algorithm could be used for the design of adaptive controllers.",

author = "Armin Shmilovici and Oded Maimon",

year = "1996",

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note = "Proceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel ; Conference date: 05-11-1996 Through 06-11-1996",

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AU - Maimon, Oded

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AB - A reduced complexity algorithm, which is an adaptive version of the Matching Pursuit algorithm, is proposed for the identification of nonlinear systems. The algorithm is demonstrated on various nonlinear systems presented in the literature. The results are favorable compared to other nonlinear identification methods (e.g. Neural Nets). It is demonstrated that the algorithm could be used for the design of adaptive controllers.

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T2 - Proceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel

Y2 - 5 November 1996 through 6 November 1996

ER -

On-line identification of nonlinear systems using adaptive matching pursuit

Abstract

Conference

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