Matrix formulation of fuzzy rule-based systems

Lotfi A., Andersen H.C. and Tsoi A.C. (1996) Matrix formulation of fuzzy rule-based systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 26 2: 332-340. doi:10.1109/3477.485885


Author Lotfi A.
Andersen H.C.
Tsoi A.C.
Title Matrix formulation of fuzzy rule-based systems
Journal name IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics   Check publisher's open access policy
ISSN 1083-4419
Publication date 1996
Sub-type Article (original research)
DOI 10.1109/3477.485885
Volume 26
Issue 2
Start page 332
End page 340
Total pages 9
Subject 2207 Control and Systems Engineering
1702 Cognitive Sciences
1709 Human-Computer Interaction
Abstract In this paper, a matrix formulation of fuzzy rule-based systems is introduced. A gradient descent training algorithm for the determination of the unknown parameters can also be expressed in a matrix form for various adaptive fuzzy networks. When converting a rule-based system to the proposed matrix formulation, only three sets of linear/nonlinear equations are required instead of set of rules and an inference mechanism. There are a number of advantages which the matrix formulation has compared with the linguistic approach. Firstly, it obviates the differences among the various architectures; and secondly, it is much easier to organize data in the implementation or simulation of the fuzzy system. The formulation will be illustrated by a number of examples.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: Scopus Import
 
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Created: Tue, 26 Jul 2016, 03:16:59 EST by System User