Neural Network Data Analysis Using Simulnet(tm)

by Edward J. Rzempoluck

Book Overview

This book and software package complements the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural network functions such as multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalised regression neural networks, learning quantizer networks, and self-organising feature maps. In an easy-to-use, Windows-based environment it...

• Format: Paperback
• Language: English
• ISBN: 1461272629
• ISBN13: 9781461272625
• Release Date: April 2013
• Publisher: Springer
• Length: 226 Pages
• Weight: 1.21 lbs.
• Dimensions: 0.5" x 8.3" x 11.0"

Customer Reviews

Useful book

I found this book to present a straightforward look into the complex world of neural networks. It is ideal for someone with little or no background in the subject yet covers sophisticated techniques as well. There were plenty of diagrams and many practical examples of how to use neural networks in the "real world." The software presents some challenges, however, given it predates Windows 98 and 2000. It seems to only work with US regional settings. Nevertheless, I was able to get it up and running and enjoyed the several examples and exercises described in the book. Overall, nicely written, an excellent introduction to the subject, and a good value.