Systems identification with fuzzy spline wavelets

Author

Shmilovici, Armin ; Maimon, Oded

Author_Institution

Dept. of Manuf. Eng., Boston Univ., MA, USA

Volume

1

fYear

1997

fDate

1-5 Jul 1997

Firstpage

299

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

Keywords

data compression; fuzzy set theory; identification; noise; nonlinear systems; splines (mathematics); wavelet transforms; FSW model; IF-THEN rules; data set compression; data set denoising; fast wavelet transform; fuzzy rule base; fuzzy spline wavelets; linguistic variables; noise; nonlinear modeling procedure; systems identification; truck backing problem; two-step process; Fuzzy sets; Fuzzy systems; Humans; Industrial engineering; Mathematical model; Pulp manufacturing; Spline; System identification; Virtual manufacturing; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on

Conference_Location

Barcelona

Print_ISBN

0-7803-3796-4

Type

conf

DOI

10.1109/FUZZY.1997.616385

Filename

616385