Сертификационные экзамены

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Principal Component Neural Networks : Theory and Applications (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)

Автор: K. I. Diamantaras, S. Y. Kung
Год: [не указано]
Издание: [не указанo]
Страниц: [не указано]
ISBN: 0471054364
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.
Добавлено: 2013-10-22 15:56:20

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