Multilayer Neural Networks

TRAMA

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. 

SOMMARIO

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.

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9783319033907
• Collana: Studies in Computational Intelligence
• Dimensioni: 235 x 155 mm
• Formato: Brossura
• Illustration Notes: XII, 182 p.
• Pagine Arabe: 182
• Pagine Romane: xii