constructive neural networks (39 résultats)

Taschenbuch. Etat : Neu. Application of Constructive Neural Networks to America's Cup Yacht | A novel performance optimization method | Frederick Courouble | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639147582 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Etat : Neu. Behavior Learning with Constructive Neural Networks in Mobile Robotics | Robot Behavior Learning: Algorithms and Experiments | Jun Li | Taschenbuch | 156 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783838380063 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Taschenbuch. Etat : Neu. Constructive Neural Networks | Leonardo Franco (u. a.) | Taschenbuch | Studies in Computational Intelligence | viii | Englisch | 2012 | Springer | EAN 9783642261084 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a collection of invited works that consider constructive methods for neural networks, taken primarily from papers presented at a special th session held during the 18 International Conference on Artificial Neural Networks (ICANN 2008) in September 2008 in Prague, Czech Republic. The book is devoted to constructive neural networks and other incremental learning algorithms that constitute an alternative to the standard method of finding a correct neural architecture by trial-and-error. These algorithms provide an incremental way of building neural networks with reduced topologies for classification problems. Furthermore, these techniques produce not only the multilayer topologies but the value of the connecting synaptic weights that are determined automatically by the constructing algorithm, avoiding the risk of becoming trapped in local minima as might occur when using gradient descent algorithms such as the popular back-propagation. In most cases the convergence of the constructing algorithms is guaranteed by the method used. Constructive methods for building neural networks can potentially create more compact and robust models which are easily implemented in hardware and used for embedded systems. Thus a growing amount of current research in neural networks is oriented towards this important topic. The purpose of this book is to gather together some of the leading investigators and research groups in this growing area, and to provide an overview of the most recent advances in the techniques being developed for constructive neural networks and their applications.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a collection of invited works that consider constructive methods for neural networks, taken primarily from papers presented at a special th session held during the 18 International Conference on Artificial Neural Networks (ICANN 2008) in September 2008 in Prague, Czech Republic. The book is devoted to constructive neural networks and other incremental learning algorithms that constitute an alternative to the standard method of finding a correct neural architecture by trial-and-error. These algorithms provide an incremental way of building neural networks with reduced topologies for classification problems. Furthermore, these techniques produce not only the multilayer topologies but the value of the connecting synaptic weights that are determined automatically by the constructing algorithm, avoiding the risk of becoming trapped in local minima as might occur when using gradient descent algorithms such as the popular back-propagation. In most cases the convergence of the constructing algorithms is guaranteed by the method used. Constructive methods for building neural networks can potentially create more compact and robust models which are easily implemented in hardware and used for embedded systems. Thus a growing amount of current research in neural networks is oriented towards this important topic. The purpose of this book is to gather together some of the leading investigators and research groups in this growing area, and to provide an overview of the most recent advances in the techniques being developed for constructive neural networks and their applications.

Etat : Sehr gut. Zustand: Sehr gut | Seiten: 291 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In behavior-based robotics, a robot achieves a required task by using various behaviors as the building blocks for that overall task. A robot behavior in turn is a sequence of sensory states and their corresponding motor actions, and extends in time and space. Making a robot able to learn (or develop) meaningful and purposeful behaviors from its own experiences has played one of the most important roles in intelligent robotics, and have been called the hallmark of intelligence. This book presents a learning system for acquiring robot behaviors by mapping sensor information directly to motor actions. It addresses the integration of three learning paradigms, namely unsupervised learning, supervised learning, and reinforcement learning. The approach is characterized by the use of constructive artificial neural networks, Several novel techniques for robot learning using constructive radial basis function networks are introduced. The learning system is verified by a number of experiments involving a real robot learning different behaviors. It is shown that the learning system is useful as a generic learning component for acquiring diverse behaviors in mobile robots. 156 pp. Englisch.

Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: courouble frederickGraduated with a Bachelor Degree in Naval Architecture innEngland, Frederick Courouble pursued his research with a Masternof Science in Aerospace Engineering in Long Beach. Its latestnresearch was in collaboration .

Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Li JunDr. Li Jun is currently with the College of Automation, Chongqing University, China. He received his PhD degree from the Center for Applied Autonomous Sensor Systems, Oerebro University, Sweden. His research interests include le.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work presents a Neural Network-based performanceanalysis and optimization of sailing configurationsof an America s Cup yacht. The analysis is based onexperimental data only, gathered from the sailingrecords provided by the onboard telemetry to trainthe neural networks. The focus of the work is on theperformance analysis, with the objective ofmaximizing boat speed (objective function) by varyingthe sailing setups (design variables). The neuralnetwork based on the experimental data is coupledwith a genetic algorithm to determine the maximumboat speed and corresponding yacht settings atvarious wind speeds. More importantly, however, the paper demonstratesthat multiple yacht sailing configurations can beanalyzed instantaneously on a regular PC, thusproviding a valuable analysis and prediction tool forthe design and sailing teams.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In behavior-based robotics, a robot achieves a required task by using various behaviors as the building blocks for that overall task. A robot behavior in turn is a sequence of sensory states and their corresponding motor actions, and extends in time and space. Making a robot able to learn (or develop) meaningful and purposeful behaviors from its own experiences has played one of the most important roles in intelligent robotics, and have been called the hallmark of intelligence. This book presents a learning system for acquiring robot behaviors by mapping sensor information directly to motor actions. It addresses the integration of three learning paradigms, namely unsupervised learning, supervised learning, and reinforcement learning. The approach is characterized by the use of constructive artificial neural networks, Several novel techniques for robot learning using constructive radial basis function networks are introduced. The learning system is verified by a number of experiments involving a real robot learning different behaviors. It is shown that the learning system is useful as a generic learning component for acquiring diverse behaviors in mobile robots.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In behavior-based robotics, a robot achieves a required task by using various behaviors as the building blocks for that overall task. A robot behavior in turn is a sequence of sensory states and their corresponding motor actions, and extends in time and space. Making a robot able to learn (or develop) meaningful and purposeful behaviors from its own experiences has played one of the most important roles in intelligent robotics, and have been called the hallmark of intelligence. This book presents a learning system for acquiring robot behaviors by mapping sensor information directly to motor actions. It addresses the integration of three learning paradigms, namely unsupervised learning, supervised learning, and reinforcement learning. The approach is characterized by the use of constructive artificial neural networks, Several novel techniques for robot learning using constructive radial basis function networks are introduced. The learning system is verified by a number of experiments involving a real robot learning different behaviors. It is shown that the learning system is useful as a generic learning component for acquiring diverse behaviors in mobile robots.

Etat : new. Questo è un articolo print on demand.

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a collection of invited works that consider constructive methods for neural networks, taken primarily from papers presented at a special th session held during the 18 International Conference on Artificial Neural Networks (ICANN 2008) in September 2008 in Prague, Czech Republic. The book is devoted to constructive neural networks and other incremental learning algorithms that constitute an alternative to the standard method of finding a correct neural architecture by trial-and-error. These algorithms provide an incremental way of building neural networks with reduced topologies for classification problems. Furthermore, these techniques produce not only the multilayer topologies but the value of the connecting synaptic weights that are determined automatically by the constructing algorithm, avoiding the risk of becoming trapped in local minima as might occur when using gradient descent algorithms such as the popular back-propagation. In most cases the convergence of the constructing algorithms is guaranteed by the method used. Constructive methods for building neural networks can potentially create more compact and robust models which are easily implemented in hardware and used for embedded systems. Thus a growing amount of current research in neural networks is oriented towards this important topic. The purpose of this book is to gather together some of the leading investigators and research groups in this growing area, and to provide an overview of the most recent advances in the techniques being developed for constructive neural networks and their applications. 293 pp. Englisch.