Multilayer Neural Networks: A Generalized Net Perspective

di Maciej Krawczak (Autore)

Springer International Publishing AG, 2013

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.  

• Autore: Maciej Krawczak
• Editore: Springer International Publishing AG
• Collana: Studies in Computational Intelligence
• Anno: 2013
• Rilegatura: Hardback
• Pagine: 182 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319002477

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