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Book synopsis

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 offers a wide range of data analytic tools which are not usually found together: genetic algorithms, probabilistic networks, as well as a number of related techniques that support these. Readers are assumed to have a basic understanding of computers and elementary mathematics, allowing them to quickly conduct sophisticated hands-on analyses of data sets.

Book details

Book category Books in English Mathematics & science Mathematics Probability & statistics

• Full title: Neural Network Data Analysis Using Simulnet (TM)
• Author: Edward J. Rzempoluck
• Language: English
• Binding: Paperback
• Number of pages: 226
• EAN: 9781461272625
• ISBN: 1461272629
• ID: 02174482
• Publisher: Springer-Verlag New York Inc.
• Weight: 600 g
• Dimensions: 280 × 210 × 14 mm
• Date of publishing: 19. April 2013

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