Neural Network Data Analysis Using Simulnet [With CDROM]

By: Edward J. Rzempoluck

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Hardcover | 12 December 1997

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Hardcover
240 Pages

Dimensions(cm)
24.77 x 19.05 x 1.91

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This book and sofwtare package provide a complement to the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural networks. Neural network functions discussed include multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalized regression neural networks, learning quantizer networks, and self-organizing feature maps. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: these include genetic algorithms, probabilistic networks, as well as a number of related techniques that support these - notably, fractal dimension analysis, coherence analysis, and mutual information analysis. The text presents a number of worked examples and case studies using Simulnet, the software package which comes with the book. Readers are assumed to have a basic understanding of computers and elementary mathematics. With this background, a reader will find themselves quickly conducting sophisticated hands-on analyses of data sets.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Neural Networks & Fuzzy Systems Databases Data Capture & Analysis Mathematics Probability & Statistics Computer Networking & Communications

Introduction	p. 1
The Simulnet Desktop	p. 5
Data Analysis	p. 13
Acquiring and Conditioning Network Data	p. 171
A Data Analysis Protocol	p. 203
Glossary	p. 213
Index	p. 219
Table of Contents provided by Blackwell. All Rights Reserved.

Neural Network Data Analysis Using Simulnet [With CDROM]

At a Glance

Hardcover

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How to return your order

Defective items

You Can Find This Book In

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