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This title in other formats:Other titles in the Neural Network Systems Techniques and Applications series:Fuzzy Logic and Expert Systems Applications (Neural Network Systems Techniques and Applications)by Cornelius T. Leondes
Synopses & ReviewsPublisher Comments:This volume covers the integration of fuzzy logic and expert systems. A vital resource in the field, it includes techniques for applying fuzzy systems to neural networks for modeling and control, systematic design procedures for realizing fuzzy neural systems, techniques for the design of rule-based expert systems using the massively parallel processing capabilities of neural networks, the transformation of neural systems into rule-based expert systems, the characteristics and relative merits of integrating fuzzy sets, neural networks, genetic algorithms, and rough sets, and applications to system identification and control as well as nonparametric, nonlinear estimation. Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as computer scientists and engineers will appreciate this reference source to diverse application methodologies. Key Features * Fuzzy system techniques applied to neural networks for modeling and control * Systematic design procedures for realizing fuzzy neural systems * Techniques for the design of rule-based expert systems * Characteristics and relative merits of integrating fuzzy sets, neural networks, genetic algorithms, and rough sets * System identification and control * Nonparametric, nonlinear estimation Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as computer scientists and engineers will find this volume a unique and comprehensive reference to these diverse application methodologies Synopsis:This volume covers the integration of fuzzy logic and expert systems. A vital resource in the field, it includes techniques for applying fuzzy systems to neural networks for modeling and control, systematic design procedures for realizing fuzzy neural systems, techniques for the design of rule-based expert systems using the massively parallel processing capabilities of neural networks, the transformation of neural systems into rule-based expert systems, the characteristics and relative merits of integrating fuzzy sets, neural networks, genetic algorithms, and rough sets, and applications to system identification and control as well as nonparametric, nonlinear estimation. Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as computer scientists and engineers will appreciate this reference source to diverse application methodologies.
Synopsis:is volume of Neural Network Systems Techniques and Applications is devoted to the integration of Fuzzy Logic and Expert Systems Applications. Table of Contentsnd Teng, Fuzzy Neural Network Systems in Model Reference Control Systems. Juditsky, Zhang, Delyon, Glorennec, and Benveniste, Wavelets in Identification.
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