Systems identification with fuzzy spline wavelets

Armin Shmilovici; Oded Maimon

Systems identification with fuzzy spline wavelets

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

Abstract

This paper describes the use of a nonlinear modeling procedure - building a Fuzzy Spline Wavelets (FSW) model. FSW models are produced with a two step process: in the first step, the data set is compressed and denoised with the use of the fast wavelet transform; and in the second stage, the results of the first stage are presented as a Fuzzy rule base with the use of linguistic variables. The hybrid model enjoys the excellent numerical and computational characteristics of the fast wavelet transform, combined with the ability to describe the accumulated knowledge in a human like way, in the form of simple IF...THEN rules using linguistic variables. The method is demonstrated for a truck backing problem.

Original language	English
Pages	299-304
Number of pages	6
State	Published - 1 Jan 1997
Externally published	Yes
Event	Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3) - Barcelona, Spain Duration: 1 Jul 1997 → 5 Jul 1997

Conference

Conference	Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3)
City	Barcelona, Spain
Period	1/07/97 → 5/07/97

ASJC Scopus subject areas

Software
Theoretical Computer Science
Artificial Intelligence
Applied Mathematics

Cite this

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title = "Systems identification with fuzzy spline wavelets",

abstract = "This paper describes the use of a nonlinear modeling procedure - building a Fuzzy Spline Wavelets (FSW) model. FSW models are produced with a two step process: in the first step, the data set is compressed and denoised with the use of the fast wavelet transform; and in the second stage, the results of the first stage are presented as a Fuzzy rule base with the use of linguistic variables. The hybrid model enjoys the excellent numerical and computational characteristics of the fast wavelet transform, combined with the ability to describe the accumulated knowledge in a human like way, in the form of simple IF...THEN rules using linguistic variables. The method is demonstrated for a truck backing problem.",

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year = "1997",

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AU - Maimon, Oded

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AB - This paper describes the use of a nonlinear modeling procedure - building a Fuzzy Spline Wavelets (FSW) model. FSW models are produced with a two step process: in the first step, the data set is compressed and denoised with the use of the fast wavelet transform; and in the second stage, the results of the first stage are presented as a Fuzzy rule base with the use of linguistic variables. The hybrid model enjoys the excellent numerical and computational characteristics of the fast wavelet transform, combined with the ability to describe the accumulated knowledge in a human like way, in the form of simple IF...THEN rules using linguistic variables. The method is demonstrated for a truck backing problem.

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M3 - Paper

AN - SCOPUS:0030654138

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T2 - Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3)

Y2 - 1 July 1997 through 5 July 1997

ER -

Systems identification with fuzzy spline wavelets

Abstract

Conference

ASJC Scopus subject areas

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