Neural Networks: Algorithms and Applications

Front Cover
Alpha Science Int'l Ltd., 2003 - Computers - 239 pages
0 Reviews
This volume provides a comprehensive introduction to the use of neural networks in mechanical engineering applications. Beginning with an overview of different neural network topologies in the first two parts, functioning of human brain is also explained as an analogy with artificial models. Unsupervised models like Hopfield, Bi-directional Associative Memory, fuzzy Associative Memory, Adaptive Resonance Theory, kohonen as well as supervised architectures like Multi-Layer Perceptron, Counter Propagation networks and Radial Basis Function Networks are presented. The third part deals with applications of artificial neural networks for solving of design optimization problems, forward and inverse dynamic analysis applications and system identification and monitoring, as well as motion and vibration control in robotics and structural engineering. Software implementations for neural networks in C/C++ language and necessary optimization techniques in network training are given in Appendices. Key Features: Latest developments in standard neural network architectures like Fuzzy ARTMAP Network models such as Probabilistic and General Regression Neural Networks (GRNN) Carefully designed simulation examples Numerical Examples
  

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

Introduction
3
Learning
17
Hopfield Perceptron and related models
35
Adaptive Resonance Theory
66
SelfOrganization Maps
82
Feedforward Back Propagation networks
94
Hybrid Learning Neural Networks
114
Probabilistic Models Fuzzy ARTMAP and Recurrent
127
Application of neural networks
157
Introduction to object oriented programming
211
Optimization schemes used in neural networks
221
Glossary
233
Copyright

Common terms and phrases

Bibliographic information