Principal Component Neural Networks: Theory and Applications by Diamantaras, K. I.

Principal Component Neural Networks: Theory and Applications (Hardcover) (ISBN-13: 9780471054368)

Vendor: K. I. Diamantaras
Product type: Books
Format: Hardcover
$210.95
$210.95
$210.95
Subtotal: $210.95
Principal Component Neural Networks: Theory and Applications by Diamantaras, K. I.

Principal Component Neural Networks: Theory and Applications

$210.95
Principal Component Neural Networks: Theory and Applications by Diamantaras, K. I.

Principal Component Neural Networks: Theory and Applications

$210.95
Format: Hardcover
Description
Description
x
Neural Network research studies how computers can be designed to emulate many of the logical and intelligent functions of the brain. The principles behind how the brain work are closely related to a statistical technique known as the Principal Component Analysis (PCA). PCA neural networks are systems that use this classical statistical technique to process information. Understanding biological perceptual systems is of great importance to engineers and computer scientists who wish to use this knowledge to develop artificial perceptual systems. This book examines the relationship between the technique of principal component analysis and neural networks. It provides a synergistic exploration of the mathematical, algorithmic, application and architectural aspects of these networks.

Author: K. I. Diamantaras, S. y. Kung
ISBN-10: 0471054364
ISBN-13: 9780471054368
Publisher: Wiley-Interscience
Language: English
Published: 03/08/1996
Pages: 272
Format: Hardcover
Weight: 1.25lbs
Size: 9.48h x 6.37w x 0.72d
By K. I. Diamantaras
By K. I. Diamantaras
x
K. I. Diamantaras is a research scientist at Aristotle University in Thessaloniki, Greece. He received his PhD from Princeton University and was formerly a research scientist for Siemans Corporate Research.

S. Y. Kung is Professor of Electrical Engineering at Princeton University and received his PhD from Stanford University. He was formerly a professor of electrical engineering at the University of Southern California.

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