Title :
Computational intelligence applied to signal processing: a proposal for fuzzy neural identification
Author :
Bottura, Celso Pascoli ; De Oliveira Serra, Ginalber Luiz
Author_Institution :
Control & Intelligent Syst. Lab., Campinas State Univ.
fDate :
Sept. 29 2004-Oct. 1 2004
Abstract :
In this study an approach to fuzzy neural identification of MIMO discrete-time nonlinear dynamical systems is proposed. Based on the Takagi-Sugeno (TS) fuzzy neural network, off-line and on-line schemes are formulated as a NARX (nonlinear autoregressive with exogenous input) fuzzy neural model from samples of a nonlinear dynamical system where the consequent parameters are modified by an adaptive WIV (weighted instrumental variable) algorithm based on the numerically robust orthogonal householder transformation
Keywords :
MIMO systems; autoregressive processes; discrete time systems; fuzzy neural nets; identification; nonlinear dynamical systems; numerical stability; signal processing; transforms; MIMO discrete-time nonlinear dynamical systems; Takagi-Sugeno fuzzy neural network; adaptive weighted instrumental variable algorithm; computational intelligence; fuzzy neural identification; nonlinear autoregressive with exogenous input; orthogonal householder transformation; signal processing; Computational intelligence; Fuzzy neural networks; Fuzzy systems; Instruments; MIMO; Nonlinear dynamical systems; Proposals; Signal processing; Signal processing algorithms; Takagi-Sugeno model;
Conference_Titel :
Machine Learning for Signal Processing, 2004. Proceedings of the 2004 14th IEEE Signal Processing Society Workshop
Conference_Location :
Sao Luis
Print_ISBN :
0-7803-8608-4
DOI :
10.1109/MLSP.2004.1422965
