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Více informací o knize Principal Component Neural Networks - Theory and Applications

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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Principal Component Neural Networks - Theory and Applications
• Autor: K. I. Diamantaras, S. Y. Kung
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 272
• EAN: 9780471054368
• ISBN: 0471054364
• ID: 04887319
• Nakladatelství: John Wiley & Sons Inc
• Hmotnost: 556 g
• Rozměry: 244 × 166 × 20 mm
• Datum vydání: 04. April 1996

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