FITSK: Online local learning with generic fuzzy input Takagi-Sugeno-Kang fuzzy framework for nonlinear system estimation

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 36, Issue 1, 2006, Pages 166-178

  Quah, Kian Hong ^a   Quek, Chai ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Degree of localization; Localized learning; Nonlinear system estimation; Takagi Sugeno Kang fuzzy models; Zero and first order TSK models

Indexed keywords

ADAPTIVE SYSTEMS; COMPUTER SIMULATION; INTERPOLATION; LEARNING ALGORITHMS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; NONLINEAR SYSTEMS; OPTIMIZATION;

DEGREE OF LOCALIZATION; LOCALIZED LEARNING; NONLINEAR SYSTEM ESTIMATION; TAKAGI-SUGENO-KANG (TSK) FUZZY MODELS;

LEARNING SYSTEMS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER PROGRAM; DECISION SUPPORT SYSTEM; FUZZY LOGIC; METHODOLOGY; NONLINEAR SYSTEM; ONLINE SYSTEM; SYSTEMS THEORY;

ALGORITHMS; DECISION SUPPORT TECHNIQUES; FUZZY LOGIC; NONLINEAR DYNAMICS; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED; SOFTWARE; SYSTEMS THEORY;

EID: 31744432525     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2005.856715     Document Type: Article

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