Description: Principles of Artificial Neural Networks, Hardcover by Graupe, Daniel, ISBN 9814522732, ISBN-13 9789814522731, Brand New, Free shipping in the US 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 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 is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks.
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Book Title: Principles of Artificial Neural Networks
Author: Graupe, Daniel
Language: english
