Neural Network Theory and MATLAB 7 Implementation

Author: Feis-tech Technology Development Center
Publisher:
Publish Date: 2005-03-01
Features:
● Basics of MATB7 and neural networks
● Neural network toolbox functions and examples for various types
● Theories and MATLAB implementations of various neural networks
● Neural network control theory and application design
● Graphical User Interface (GUI) for neural networks
● Fault diagnosis based on neural networks
● Prediction based on neural networks
● Fuzzy control based on neural networks
● Adaptive noise cancellation technology based on neural networks.
Target Audience: This book can serve as a supplementary textbook for senior undergraduate and graduate students in science and engineering disciplines studying neural networks. It can also be used as a reference for researchers and practitioners in this field. As one of the "MATLAB Application Technology" series, this book is based on the newly released Neural Network Toolbox 4.0.3 for MATLAB 7. The first two chapters introduce the basics of MATLAB 7 and neural networks, providing a detailed classification and introduction of important functions in the neural network toolbox, along with complete examples. From Chapter 3 to Chapter 5, several important types of neural networks are introduced, including perceptrons, linear networks, and BP networks, along with their structures, learning algorithms, and MATLAB implementations. Chapter 6 covers the graphical user interface for neural networks. The last five chapters discuss how to use the neural network toolbox to solve practical problems in application areas such as control, fault diagnosis, prediction, and active noise cancellation. This book can serve as a supplementary textbook for senior undergraduate and graduate students in science and engineering disciplines studying neural networks, or as a reference for researchers and practitioners in this field.