Principal Component Neural Networks
Author | : K. I. Diamantaras |
Publisher | : Wiley-Interscience |
Total Pages | : 282 |
Release | : 1996-03-08 |
ISBN-10 | : UOM:39015037330696 |
ISBN-13 | : |
Rating | : 4/5 (96 Downloads) |
Download or read book Principal Component Neural Networks written by K. I. Diamantaras and published by Wiley-Interscience. This book was released on 1996-03-08 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical, algorithmic, application and architectural aspects of principal component neural networks. Using a unified formulation, the authors present neural models performing PCA from the Hebbian learning rule and those which use least squares learning rules such as back-propagation. Examines the principles of biological perceptual systems to explain how the brain works. Every chapter contains a selected list of applications examples from diverse areas.