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Aggiungi al carrelloCondizione: Gut. Zustand: Gut | Seiten: 580 | Sprache: Englisch | Produktart: Bücher | Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book. On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented. For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.
Lingua: Inglese
Editore: Kluwer Academic Publishers, 1992
ISBN 10: 079239268X ISBN 13: 9780792392682
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Aggiungi al carrelloCondizione: New. Presents an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. This book is useful to workers in connectionism, and to students of sensormonitor control in living systems. Editor(s): Bekey, George A.; Goldberg, Kenneth Y. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 575 pages, biography. BIC Classification: TJFM1. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 31. Weight in Grams: 984. . 1992. Hardback. . . . .
Condizione: New. pp. 580.
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book. On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented. For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.
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Aggiungi al carrelloHardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Lingua: Inglese
Editore: Kluwer Academic Publishers, 1992
ISBN 10: 079239268X ISBN 13: 9780792392682
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Condizione: New. Presents an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. This book is useful to workers in connectionism, and to students of sensormonitor control in living systems. Editor(s): Bekey, George A.; Goldberg, Kenneth Y. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 575 pages, biography. BIC Classification: TJFM1. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 31. Weight in Grams: 984. . 1992. Hardback. . . . . Books ship from the US and Ireland.
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems pr.
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book. On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented. For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems. 580 pp. Englisch.
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Aggiungi al carrelloBuch. Condizione: Neu. Neural Networks in Robotics | George A. Bekey (u. a.) | Buch | The Springer International Series in Engineering and Computer Science | xii | Englisch | 1992 | Springer | EAN 9780792392682 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Springer, Springer Nov 1992, 1992
ISBN 10: 079239268X ISBN 13: 9780792392682
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book.On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented.For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 580 pp. Englisch.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 276,80
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 580.
Da: Majestic Books, Hounslow, Regno Unito
EUR 294,39
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 580 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.