Neural Network Simulation Classes
	for the NeXT Computer
		By: Ralph Zazula
		University of Arizona
		zazula@bonehead.tucson.az.us
(NeXT Mail)		

Jan 10, 1992
		
	This package contains Classes that can be used to create software simulations of neural network architectures.  These were written by me for use in my research with the goal of rapid creation of code to explore various network topologies and learning algorithms.  I would like to hear input from people using these ± especially if you have found errors or have improvements ± or just to hear what NeXTy things you are doing in your neural-network research. 
		
	You cannot use these for commercial purposes.
	
The classes contained are:

  Neuron		Implements a number of different types of
		neurons
  BackPropEngine	Implements a back-propagation network
  
The file bptest.m shows an example of using the BackPropEngine class to learn the identity function.  The file boltz.m uses a fully-connected boltzman machine to learn the XOR problem.

Take note of the SYMMETRIC definition in Neuron.h.  I will be making a cleaner interface to the weights in the near future but for now you must change the define accordingly.

Most everything else is documented through the Class descriptions, code or example programs.  If you have any questions/comments, feel free to e-mail me.

Ralph Zazula