A comprehensive introduction to the most popular class of neural network, the multilayer perceptron, showing how it can be used for system identification and control. The book provides readers with a sufficient theoretical background to understand the characteristics of different methods, and to be aware of the pit-falls so as to make the correct decisions in all situations. This is a very application-oriented text that gives detailed and pragmatic recommendations to guide users through the plethora of methods suggested in the literature. Furthermore, it introduces sound working procedures that can lead to efficient neural network solutions. Invaluable to the practitioner and as a textbook in courses with a significant hands-on component.
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A comprehensive introduction to the most popular class of neural network, the multilayer perceptron, showing how it can be used for system identification and control. The book provides readers with a sufficient theoretical background to understand the characteristics of different methods, and to be aware of the pit-falls so as to make the correct decisions in all situations. This is a very application-oriented text that gives detailed and pragmatic recommendations to guide users through the plethora of methods suggested in the literature. Furthermore, it introduces sound working procedures that can lead to efficient neural network solutions. Invaluable to the practitioner and as a textbook in courses with a significant hands-on component.
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Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
Paperback. Condición: Good. 2000. Corr. 3rd. 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. Nº de ref. del artículo: 1852332271-11-1
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Librería: Greenworld Books, Arlington, TX, Estados Unidos de America
Condición: 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. Nº de ref. del artículo: GWV.1852332271.G
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Librería: HPB-Red, Dallas, TX, Estados Unidos de America
Paperback. Condición: 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! Nº de ref. del artículo: S_331296964
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Librería: Better World Books Ltd, Dunfermline, Reino Unido
Condición: Good. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages. Nº de ref. del artículo: 45648644-20
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Librería: GoldBooks, Denver, CO, Estados Unidos de America
Condición: new. Nº de ref. del artículo: 37G62_25_1852332271
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Condición: New. Nº de ref. del artículo: ABLIING23Mar2912160256523
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9781852332273_new
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Librería: Chiron Media, Wallingford, Reino Unido
PF. Condición: New. Nº de ref. del artículo: 6666-IUK-9781852332273
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 264 pp. Englisch. Nº de ref. del artículo: 9781852332273
Cantidad disponible: 2 disponibles
Librería: BennettBooksLtd, San Diego, NV, Estados Unidos de America
Paperback. Condición: New. In shrink wrap. Looks like an interesting title! Nº de ref. del artículo: Q-1852332271
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