
The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti?cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful ability to routinely make accurate complex, nonlinear models of such ill-understood phenomena as physical, economic, social, and information-based time series and signals and of the patterns h- den i ...
DETAILS
Feedforward Neural Network Methodology
Fine, Terrence L.
Gebunden, xvi, 340 S.
XVI, 340 p.
Sprache: Englisch
235 mm
ISBN-13: 978-0-387-98745-3
Titelnr.: 94775362
Gewicht: 730 g
Springer, Berlin (1999)
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Springer Heidelberg
Tiergartenstr. 17
69121 - DE Heidelberg
E-Mail: buchhandel-buch@springer.com