A new pseudo-Gaussian-based recurrent fuzzy CMAC model for dynamic systems processing

DOI10.1080/00207720701792339zbMath1168.93414OpenAlexW2014872489MaRDI QIDQ3497772

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Publication date: 27 July 2009

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207720701792339

zbMATH Keywords

identificationcerebellar model articulation controlleron-line learningrecurrent networkpseudo-Gaussian basis function

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Fuzzy control/observation systems (93C42) Identification in stochastic control theory (93E12) Stochastic learning and adaptive control (93E35)

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A hybrid of electromagnetism-like mechanism and back-propagation algorithms for recurrent neural fuzzy systems design

Cites Work

• CMAC neural networks for control of nonlinear dynamical systems: Structure, stability and passivity
• An asymmetry-similarity-measure-based neural fuzzy inference system
• Data Storage in the Cerebellar Model Articulation Controller (CMAC)
• A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)
• Linear splines with adaptive mesh sizes for modelling nonlinear dynamic systems
• A hybrid fuzzy cerebellar model articulation controller based autonomous controller

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