Deterministic learning theory identification par wang cong (22 résultats)

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Etat : New.

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Etat : As New. Unread book in perfect condition.

Paperback. Etat : Brand New. 207 pages. 9.21x6.14x0.87 inches. In Stock.

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Etat : New. pp. xix + 195 1st Edition.

HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Etat : New. Provides systematic design approaches for the identification, control, and recognition of nonlinear systems in uncertain environments. This book introduces the concepts of deterministic learning theory and then discusses the persistent excitation property of RBF networks. Series Editor(s): Lewis, Frank L. Series: Automation and Control Engineering. Num Pages: 207 pages, 147 black & white illustrations. BIC Classification: UYQE. Category: (P) Professional & Vocational. Dimension: 243 x 164 x 20. Weight in Grams: 508. . 2009. Hardback. . . . .…

Hardcover. Etat : New.

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Hardback. Etat : New. Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way. A Deterministic View of Learning in Dynamic EnvironmentsThe authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems. A New Model of Information ProcessingThis book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).…

Etat : New.

Etat : New. Provides systematic design approaches for the identification, control, and recognition of nonlinear systems in uncertain environments. This book introduces the concepts of deterministic learning theory and then discusses the persistent excitation property of RBF networks. Series Editor(s): Lewis, Frank L. Series: Automation and Control Engineering. Num Pages: 207 pages, 147 black & white illustrations. BIC Classification: UYQE. Category: (P) Professional & Vocational. Dimension: 243 x 164 x 20. Weight in Grams: 508. . 2009. Hardback. . . . . Books ship from the US and Ireland.…

Etat : New. Cong Wang, David J. HillDeterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic envi.

Hardback. Etat : New. Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way. A Deterministic View of Learning in Dynamic EnvironmentsThe authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems. A New Model of Information ProcessingThis book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).…

Hardcover. Etat : Brand New. 1st edition. 207 pages. 9.53x6.30x0.71 inches. In Stock.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Cong Wang, David J. HillDeterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic envi.…

Etat : New. pp. xix + 195 Illus. This item is printed on demand.

Hardcover. Etat : Brand New. 1st edition. 207 pages. 9.53x6.30x0.71 inches. In Stock. This item is printed on demand.