Technical report available by anonymous ftp

[gfh@eng.cam.ac.uk]

The following technical report is available by anonymous ftp from the
archive of the Speech, Vision and Robotics Group at the Cambridge
University Engineering Department.

                EXPERIMENTS WITH SIMPLE HEBBIAN-BASED
            LEARNING RULES IN PATTERN-CLASIFICATION TASKS

               George F. Harpur and Richard W. Prager

                Technical Report CUED/F-INFENG/TR168

	    Cambridge University Engineering Department 
		        Trumpington Street 
		        Cambridge CB2 1PZ 
			     England 


                             Abstract

This report presents a neural network architecture which performs
pattern classification using a simple form of learning based on the
Hebb rule.  The work was motivated by the desires to decrease
computational complexity and to maintain a greater degree of
biological plausibility than most other networks designed to perform
similar tasks.  A method of pre-processing the inputs to provide a
distributed representation is described.  A scheme for increasing the
power of the network using a layer of `feature detectors' is
introduced: these use an unsupervised competitive learning scheme,
again based on Hebbian learning.  Simulation results from testing the
networks on two `real-world' problems are presented, and compared to
those produced by other types of neural network.


************************ How to obtain a copy ************************

Via FTP:

unix> ftp svr-ftp.eng.cam.ac.uk
Name: anonymous
Password: (type your email address)
ftp> cd reports
ftp> binary
ftp> get harpur_tr168.ps.Z
ftp> quit
unix> uncompress harpur_tr168.ps.Z
unix> lpr harpur_tr168.ps (or however you print PostScript)