[PDF.46sv] Principal Component Neural Networks: Theory and Applications

Principal Component Neural Networks: Theory and Applications

[PDF.um83] Principal Component Neural Networks: Theory and Applications

Principal Component Neural Networks:  K. I. Diamantaras, S. Y. Kung epub
Principal Component Neural Networks:  K. I. Diamantaras, S. Y. Kung pdf download
Principal Component Neural Networks:  K. I. Diamantaras, S. Y. Kung pdf file
Principal Component Neural Networks:  K. I. Diamantaras, S. Y. Kung audiobook
Principal Component Neural Networks:  K. I. Diamantaras, S. Y. Kung book review
Principal Component Neural Networks:  K. I. Diamantaras, S. Y. Kung summary

 | #4294334 in Books |  1996-03-08 | Original language:English | PDF # 1 |  9.49 x.79 x6.34l,1.25 | File type: PDF | 272 pages

---

||0 of 1 people found the following review helpful.| Explains Neural Networks architecture clearly|By Sophia|This book explains the application of Neural Networks into Principal Component Analysis with clear logic and easy examples. The only problem is that I still think this book is too succinct. I'll have to find papers to see the updating rule for some parameters. But as the first step to understand this topic, this book is go|From the Publisher|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 n

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 p...

You can specify the type of files you want, for your gadget.Principal Component Neural Networks: Theory and Applications   |  K. I. Diamantaras, S. Y. Kung. A good, fresh read, highly recommended.

Download Now