From: mason@friartuck.cs.uregina.ca (Ralph Mason)
Subject: Principal Component Analysis
Summary: list of references 
Date: Tue, 15 Dec 1992 12:39:28 GMT
Organization: University of Regina
Keywords: Principal Component Analysis

As promised, I am posting all the references I received on
PCA.  I thank everyone for their response.


Cottrell, Munro, Zipser, "Learning Internal representations from
Gray-Scale Images: An example of Representational Programming," 9th
Ann. Conf fo the Cognitive Science Society, July 16-18, 1987, pp 462-473

Cottrell, Munro, "Principal Components of Images via Back
Propagation," SPIE Vol 1001: Visual Communications and Image
Processing '88, pp 1070-1077

Cottrell, Metcalfe, "EMPATH:  Face, Emotion and Gender Recognition
Using Holons", Advances in Neural Information Processing Systems 3,
1991, pp 564-571

Golomb, Lawrence, Sejnowski, "SEXNET:  A Neural Network Identifies Sex
>From Human Faces," Advances in Neural Information Processing Systems
3, 1991, pp 572-577

Russo, Real, "Image Compression Using an Outer Product Neural
Network," ICASSP 1992, pp II-377-380

Sicuranza, Ramponi, Marsi, "Artificial Neural Networks for Image
Compression,"  Electronics Letters Vol 26 No 7, 1990, pp 477-479

Oja, "A Simplified Neuron Model as a Principal Component Analyzer", J.
Math. Biology Vol 15, 1982, pp 267-273

Oja, Karhunen, "On Stochastic Approximation of the Eigenvectors and
Eigenvalues of the Expectation of a Random Matrix,"  J of Math.
Analysis and Applications, Vol 106, 1985, pp 69-64

Oja, "Neural Networks, Principal Components, and Subspaces,"  Int. J.
of Neural Systems, Vol 1, No 1 , 1989, pp 61-68

Xu, Yuille, "Robust Principal Component Analysis by Self-Organizing
Rules Based on Statistical Physics Approach,"  Harvard Robotics
Laboratory:  Technical Report No 92-3, Feb 1992

Sanger, "Optimal Unsupervised Learning in a Single-Layer Linear
Feedforward Neural Network,"  Neural Networks, Vol 2, 1989, pp 459-473

Sanger, "An Optimality Principle for Unsupervised Learning,"  Advances
in Neural Information Processing Systems 1, 1989, pp 11-19

Sanger, "Analysis of the Two-Dimensional Receptive Fields Learned by
the Generalized Hebbian Algorithm in Response to Random Input", Biol.
Cybern Vol 63, 1990, pp 221-228

I use (rather than understand :-) PCA for the analysis of
the dynamic systems embodied by recurrent NNs.  If you need
practical advice to software to do it, I recommend Splus
(see prcomp())

 -- Fred
fcummins@ucs.indiana.edu

	"Principal Component Analysis: A Beginner's Guide"
	by Ian T.Jolliffe.
	Weather, October 1990, (Vol. 45 No.10).

For more indepth mathematical explainations other references would be more
appropriate.  Also there is an eigen vector analysis routine in the NAG
library which can do the analysis for you.


+----------------- mason@robinhood.engg.uregina.ca ----------------------+
|   Dr. Ralph Mason                            University of Regina      |
|   Assistant Professor                        Regina, Saskatchewan      |
|   Faculty of Engineering                     Canada, S4S 0A2           |
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