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Used book that is in excellent condition. May show signs of wear or have minor defects. Seller Inventory # 18155427-6
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 Environments
The 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 Processing
This 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).
About the Author: Cong Wang, David J. Hill
Title: Deterministic Learning Theory for ...
Publisher: CRC Press LLC
Publication Date: 2009
Binding: Hardcover
Condition: Very Good
Edition: 1st Edition.
Seller: moluna, Greven, Germany
Gebunden. Condition: 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. Seller Inventory # 595092857
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 5739241-n
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Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Seller: California Books, Miami, FL, U.S.A.
Condition: New. Seller Inventory # I-9780849375538
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 5739241
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Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 5739241
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. Deterministic Learning Theory for Identification, Recognition, and Control | Cong Wang (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2009 | CRC Press | EAN 9780849375538 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 133231865
Seller: UK BOOKS STORE, London, LONDO, United Kingdom
Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability. Seller Inventory # CBS 9780849375538
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Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Offering a new perspective, this book provides systematic design approaches for the identification, control, and recognition of nonlinear systems in uncertain environments. It introduces the concepts of deterministic learning theory and then discusses the persistent excitation property of RBF networks. The authors describe the theory of deterministic learning processes and address dynamical pattern recognition and pattern-based control processes. They present a new model of dynamical parallel distributed processing applicable to the detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems. Seller Inventory # 9780849375538