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Engineering - Computational Intelligence and Complexity | Multilayer Neural Networks - A Generalized Net Perspective

Multilayer Neural Networks

A Generalized Net Perspective

Krawczak, Maciej

2013, XII, 182 p. 35 illus.

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  • Recent research on Multilayer Neural Networks
  • Shows that a multilayer neural network can be considered as a multistage system, and that the learning of this class of neural networks can be treated as a special sort of the optimal control problem
  •  
  • Presents a new way to describe the functioning of discrete dynamic systems
  • Shows that the generalized net theory developed by Atanassov (1984) as the extension of the ordinary Petri net theory and its modifications can be successfully used as a new description of multilayer neural networks

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.

 

Content Level » Research

Keywords » Computational Intelligence - Discrete Dynamic Systems - Multilayer Neural Networks - Neural Networks - Optimal Control

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity - Control Engineering

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.

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