Multilayer neural networks : a generalized Net perspective

The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, li...

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מחבר ראשי: Krawczak, Maciej, 19..-
פורמט: Livre numérique
שפה:Anglais
יצא לאור: Cham : Springer International Publishing [20..].
Cham : Springer Nature
מהדורה:1st ed. 2013.
סדרה:Studies in Computational Intelligence 478
גישה מקוונת:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
הערה: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Multilayer Neural Networks, Texte imprimé, 9783319002477
• Multilayer Neural Networks, Texte imprimé, 9783319002491
• Multilayer Neural Networks, Texte imprimé, 9783319033907
• Multilayer Neural Networks, Texte imprimé, 9783319002477
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245 1 0 |a Multilayer neural networks :  |b a generalized Net perspective   |c by Maciej Krawczak. 
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505 1 |a Introduction to Multilayer Neural Networks Basics of Generalized Nets Simulation Process of Neural Networks Learning from Examples Learning as a Control Process Parameterisation of Learning Adjoint Neural Networks 
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506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, like dynamic programming, with modifications, can yield a new class of learning algorithms for multilayer neural networks. Another purpose of this book is to show that the generalized net theory can be successfully used as a new description of multilayer neural networks. Several generalized net descriptions of neural networks functioning processes are considered, namely: the simulation process of networks, a system of neural networks and the learning algorithms developed in this book.The generalized net approach to modelling of real systems may be used successfully for the description of a variety of technological and intellectual problems, it can be used not only for representing the parallel functioning of homogenous objects, but also for modelling non-homogenous systems, for example systems which consist of a different kind of subsystems.The use of the generalized nets methodology shows a new way to describe functioning of discrete dynamic systems.  
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