Description

Book Synopsis
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.

Table of Contents
A Review of Linear Algebra.

Principal Component Analysis.

PCA Neural Networks.

Channel Noise and Hidden Units.

Heteroassociative Models.

Signal Enhancement Against Noise.

VLSI Implementation.

Appendices.

Bibliography.

Index.

Principal Component Neural Networks

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    A Hardback by K. I. Diamantaras, S. Y. Kung

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      Publisher: Wiley
      Publication Date: Publication Date: 04/04/1996
      ISBN13: 9780471054368, 978-0471054368
      ISBN10:

      Description

      Book Synopsis
      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.

      Table of Contents
      A Review of Linear Algebra.

      Principal Component Analysis.

      PCA Neural Networks.

      Channel Noise and Hidden Units.

      Heteroassociative Models.

      Signal Enhancement Against Noise.

      VLSI Implementation.

      Appendices.

      Bibliography.

      Index.

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