NDLI: Modular structure of fuzzy system modeling using wavelet networks

Content Provider	IEEE Xplore Digital Library
Author	Yuetong Lin Fei-Yue Wang
Copyright Year	2005
Description	Author affiliation: Dept. of Syst. & Ind. Eng., Arizona Univ., Tucson, AZ, USA (Yuetong Lin; Fei-Yue Wang)
Abstract	This paper proposes a novel approach to constructing fuzzy logic control system using the combination of wavelet network and feedforward BP networks. Numerous works have been reported on the integration, of fuzzy logic systems and neural networks; however most of these hybridizations have resulted in the loss of the original knowledge structure embedded in its network implementation. Due to the inherent modularity, the decision-making process of a fuzzy logic control system can be readily partitioned into three functionally independent modules, namely pattern recognition, fuzzy reasoning and control synthesis, and therefore individual subnets can be built to implement these modules as subnets for the overall feedforward networks. Both wavelet network and BP feedforward network are adopted for the construction of the subnets so that the local receptive field-type wavelet networks with orthogonal least square learning algorithm are capable to capture the fine details of the underlying dynamics, and the overall feedforward structure with the BP algorithm is responsible for the global optimization of the networks parameters. Simulation also shows its superiority.
Starting Page	671
Ending Page	676
File Size	1003721
Page Count	6
File Format	PDF
ISBN	0780388127
DOI	10.1109/ICNSC.2005.1461270
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy systems Fuzzy logic Control system synthesis Control systems Neural networks Decision making Pattern recognition Fuzzy reasoning Network synthesis Least squares methods
Content Type	Text
Resource Type	Article

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