Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems

Computers and Mathematics with Applications

Volumn 56, Issue 12, 2008, Pages 3157-3164

  Wang, Dongqing ^a   Ding, Feng ^b  

^a QINGDAO UNIVERSITY   (China)

^b JIANGNAN UNIVERSITY   (China)

Author keywords

Convergence properties; Forgetting factor; Hammerstein Wiener systems; Parameter estimation; Stochastic gradient

Indexed keywords

COMMUNICATION CHANNELS (INFORMATION THEORY); LEARNING SYSTEMS; MEATS; METAL ANALYSIS; MODEL STRUCTURES; PARAMETER ESTIMATION; SINGULAR VALUE DECOMPOSITION; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC MODELS;

ARMAX MODELS; AVERAGE METHODS; BASIC IDEAS; CONVERGENCE PROPERTIES; FORGETTING FACTOR; FORGETTING FACTORS; HAMMERSTEIN-WIENER SYSTEMS; IDENTIFICATION ACCURACIES; IDENTIFICATION ALGORITHMS; IDENTIFICATION MODELS; INFORMATION VECTORS; NOISE TERMS; ORIGINAL SYSTEMS; PARAMETER ESTIMATES; PARAMETER ESTIMATION ERRORS; PRODUCT TERMS; SIMULATION RESULTS; SINGULAR VALUE DECOMPOSITION METHODS; STOCHASTIC GRADIENT; STOCHASTIC GRADIENT ALGORITHMS; STOCHASTIC GRADIENTS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 55649109065     PISSN: 08981221     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.camwa.2008.07.015     Document Type: Article

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