MATLAB & Simulink Based Books

Neural Network Design

		Martin T. Hagan, Oklahoma State University Howard B. Demuth, University of Idaho Mark Beale, MHB, Inc Martin/Hagan (Distributed by the University of Colorado), 1996 Tel:  303-492-3648 ISBN: 0-9717321-0-8 Language: English

This text provides a clear and detailed survey of basic neural network architectures and learning rules. The authors emphasize mathematical analysis of networks, methods for training networks, and application of networks to practical engineering problems in pattern recognition, signal processing, and control systems. Background material, such as linear algebra, optimization, and stability, is provided. Simple building blocks are used to explain associative and competitive networks. They include feature maps, learning vector quantization, and adaptive resonance theory. Examples and solved problems are included with optional exercises incorporating the use of MATLAB.  An instructor's manual is available for adopters of this text.

Companion Software: A set of M-files and transparency masters are available. Retrieve companion software