Principal Component Neural Networks
Theory and Applications
AvK. I. Diamantaras,S. Y. Kung
Inbunden, Engelska, 1996
Del 4 i serien Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
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Beskrivning
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.