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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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Krawczak, Maciej (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Studies in Computational Intelligence, 478
Temas:
Acceso en línea:Texto Completo

MARC

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300 |a XII, 182 p.  |b online resource. 
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490 1 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 478 
505 0 |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. 
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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