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Because of massively parallel distributed nature and very fast convergence rates, recurrent neural networks (RNN) are widely applied to solving many problems in optimization, control and robotic systems, etc. Hence, this book investigates the following RNN models which solve some practical problems, together with their corresponding analysis on stability and convergence. A type of multilayer pole-assignment neural networks is applied to online synthesizing and tuning feedback control systems. Then, a novel RNN model is established by absorbing the first-order time-derivative information to solve the Sylvester equation with time-varying coefficient matrices. A dual neural network is developed to handle quadratic programs subject to linear constraints. The Lagrangian neural network and primal-dual neural network are also reviewed for comparison purposes. The neural networks are then exploited for real-time motion planning of redundant manipulators. The publication is primarily intended for researchers and postgraduates studying in RNN, control and robotics.
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L'autore
Yunong Zhang is a professor at School of Information Science and Technology, Sun Yat-Sen University (SYSU), China. Before joining SYSU, he had been with National University of Ireland, University of Strathclyde, National University of Singapore, Chinese University of Hong Kong, since 1999. His main research interests are neural networks.
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Recurrent Neural Networks
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Zhang YunongYunong Zhang is a professor at School of Information Science and Technology, Sun Yat-Sen University (SYSU), China. Before joining SYSU, he had been with National University of Ireland, University of Strathclyde, National . Codice articolo 5411115
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Recurrent Neural Networks
Editore:
LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Because of massively parallel distributed nature and very fast convergence rates, recurrent neural networks (RNN) are widely applied to solving many problems in optimization, control and robotic systems, etc. Hence, this book investigates the following RNN models which solve some practical problems, together with their corresponding analysis on stability and convergence. A type of multilayer pole-assignment neural networks is applied to online synthesizing and tuning feedback control systems. Then, a novel RNN model is established by absorbing the first-order time-derivative information to solve the Sylvester equation with time-varying coefficient matrices. A dual neural network is developed to handle quadratic programs subject to linear constraints. The Lagrangian neural network and primal-dual neural network are also reviewed for comparison purposes. The neural networks are then exploited for real-time motion planning of redundant manipulators. The publication is primarily intended for researchers and postgraduates studying in RNN, control and robotics. 200 pp. Englisch. Codice articolo 9783838303826
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Recurrent Neural Networks : Design, Analysis, Applications to Control and Robotic Systems
Editore:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Because of massively parallel distributed nature and very fast convergence rates, recurrent neural networks (RNN) are widely applied to solving many problems in optimization, control and robotic systems, etc. Hence, this book investigates the following RNN models which solve some practical problems, together with their corresponding analysis on stability and convergence. A type of multilayer pole-assignment neural networks is applied to online synthesizing and tuning feedback control systems. Then, a novel RNN model is established by absorbing the first-order time-derivative information to solve the Sylvester equation with time-varying coefficient matrices. A dual neural network is developed to handle quadratic programs subject to linear constraints. The Lagrangian neural network and primal-dual neural network are also reviewed for comparison purposes. The neural networks are then exploited for real-time motion planning of redundant manipulators. The publication is primarily intended for researchers and postgraduates studying in RNN, control and robotics. Codice articolo 9783838303826
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Recurrent Neural Networks
Editore:
LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Because of massively parallel distributed nature and very fast convergence rates, recurrent neural networks (RNN) are widely applied to solving many problems in optimization, control and robotic systems, etc. Hence, this book investigates the following RNN models which solve some practical problems, together with their corresponding analysis on stability and convergence. A type of multilayer pole-assignment neural networks is applied to online synthesizing and tuning feedback control systems. Then, a novel RNN model is established by absorbing the first-order time-derivative information to solve the Sylvester equation with time-varying coefficient matrices. A dual neural network is developed to handle quadratic programs subject to linear constraints. The Lagrangian neural network and primal-dual neural network are also reviewed for comparison purposes. The neural networks are then exploited for real-time motion planning of redundant manipulators. The publication is primarily intended for researchers and postgraduates studying in RNN, control and robotics.Books on Demand GmbH, Überseering 33, 22297 Hamburg 200 pp. Englisch. Codice articolo 9783838303826
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Recurrent Neural Networks
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Da: Books Puddle, New York, NY, U.S.A.
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Condizione: New. pp. 200. Codice articolo 26128855531
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Recurrent Neural Networks
Editore:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Da: Majestic Books, Hounslow, Regno Unito
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Condizione: New. Print on Demand pp. 200 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Codice articolo 131699252
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Recurrent Neural Networks
Editore:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Condizione: New. PRINT ON DEMAND pp. 200. Codice articolo 18128855521
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Recurrent Neural Networks: Design, Analysis, Applications to Control and Robotic Systems
Editore:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838303822
ISBN 13: 9783838303826
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Paperback. Condizione: Like New. Like New. book. Codice articolo ERICA79038383038226
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