Multilayer neural networks : a generalized net perspective
Author(s)
Bibliographic Information
Multilayer neural networks : a generalized net perspective
（Studies in computational intelligence, 478）
Springer, c2013
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Note
Includes bibliographical references
Description and Table of Contents
Description
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.
Table of Contents
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.
by "Nielsen BookData"
