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It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience. N° de réf. du vendeur 1852332271-11-1
The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component.
Titre : Neural Networks for Modelling and Control of...
Éditeur : Springer (edition 2000. Corr. 3rd)
Date d'édition : 2000
Reliure : Paperback
Etat : Good
Edition : 2000. Corr. 3rd.
Vendeur : HPB-Red, Dallas, TX, Etats-Unis
Paperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_331296964
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Vendeur : Better World Books Ltd, Dunfermline, Royaume-Uni
Etat : Good. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages. N° de réf. du vendeur 45648644-20
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Vendeur : Greenworld Books, Arlington, TX, Etats-Unis
Etat : good. Fast Free Shipping â" Good condition book with a firm cover and clean, readable pages. Shows normal use, including some light wear or limited notes highlighting, yet remains a dependable copy overall. Supplemental items like CDs or access codes may not be included. N° de réf. du vendeur GWV.1852332271.G
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Vendeur : Buchpark, Trebbin, Allemagne
Etat : Gut. Zustand: Gut | Seiten: 264 | Sprache: Englisch | Produktart: Bücher | The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component. N° de réf. du vendeur 694/3
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Vendeur : GoldBooks, Denver, CO, Etats-Unis
Etat : new. N° de réf. du vendeur 37G62_25_1852332271
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Neural networks are of increasing interest to control engineersOf the several books available on this subject none is an advanced textbookA comprehensive introduction to the most popular class of neural network, the multilayer perceptron, showing ho. N° de réf. du vendeur 4289421
Quantité disponible : Plus de 20 disponibles
Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Neural Networks for Modelling and Control of Dynamic Systems | A Practitioner's Handbook | M. Norgaard (u. a.) | Taschenbuch | xiv | Englisch | 2000 | Springer London | EAN 9781852332273 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 106306674
Quantité disponible : 5 disponible(s)
Vendeur : Chiron Media, Wallingford, Royaume-Uni
PF. Etat : New. N° de réf. du vendeur 6666-IUK-9781852332273
Quantité disponible : 10 disponible(s)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar2912160256523
Quantité disponible : Plus de 20 disponibles
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. Neuware -The technology of neural networks has attracted much attention in recentyears. Their ability to learn nonlinear relationships is widelyappreciated and is utilized in many different types of applications;modelling of dynamic systems, signal processing, and control system designbeing some of the most common. The theory of neural computing has maturedconsiderably over the last decade and many problems of neural networkdesign, training and evaluation have been resolved. This book provides acomprehensive introduction to the most popular class of neural networkthe multilayer perceptron, and shows how it can be used for systemidentification and control. It aims to provide the reader with asufficient theoretical background to understand the characteristics ofdifferent methods, to be aware of the pit-falls and to make properdecisions in all situations. The subjects treated include:System identification: multilayer perceptrons; how to conduct informativeexperiments; model structure selection; training methods; modelvalidation; pruning algorithms.Control: direct inverse, internal model, feedforward, optimal andpredictive control; feedback linearization andinstantaneous-linearization-based controllers.Case studies: prediction of sunspot activity; modelling of a hydraulicactuator; control of a pneumatic servomechanism; water-level control in aconical tank.The book is very application-oriented and gives detailed and pragmaticrecommendations that guide the user through the plethora of methodssuggested in the literature. Furthermore, it attempts to introduce soundworking procedures that can lead to efficient neural network solutions.This will make the book invaluable to the practitioner and as a textbookin courses with a significant hands-on component.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 264 pp. Englisch. N° de réf. du vendeur 9781852332273
Quantité disponible : 2 disponible(s)