CHF 196.00

Principles Of Artificial Neural Networks (3rd Edition)

English · Hardback

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Description

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Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond.

This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained.

The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks.


Product details

Authors Daniel Graupe, Daniel Graupe, Graupe Daniel
Publisher World Scientific Publishing
 
Content Book
Product form Hardback
Publication date 18.09.2013
Subject Natural sciences, medicine, IT, technology > IT, data processing > IT
 
EAN 9789814522731
ISBN 978-981-45227-3-1
Pages 384
Illustrations Illustrations (black and white)
 
Series Advanced Circuits and Systems > 7
Advanced Series In Circuits And Systems > 7
Subjects COMPUTERS / Data Science / Neural Networks
Neural networks and fuzzy systems
Neural networks & fuzzy systems
 

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