PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS (3RD EDITION) (Advanced Series in Circuits and Systems, 7)

Graupe, Daniel

ISBN 10: 9814522732 / ISBN 13: 9789814522731

Edité par World Scientific Pub Co Inc, 2013

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Synopsis :

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. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.

Détails bibliographiques

Titre : PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS (...
Éditeur : World Scientific Pub Co Inc
Date d'édition : 2013
Reliure : Couverture rigide
Etat : Neuf
Edition : 3ème Édition