Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!ncar!tank!eecae!frey
From: frey@eecae.UUCP (Zachary Frey)
Newsgroups: comp.ai.neural-nets
Subject: Size limits of BP (Was Re: ART and non-stationary environments)
Keywords: BP
Message-ID: <15313@eecae.UUCP>
Date: 2 May 89 18:21:52 GMT
References: <18589@gatech.edu>
Reply-To: frey@eecae.UUCP (Zachary Frey)
Organization: Michigan State University, ERDL
Lines: 24

In article <18589@gatech.edu> myke@gatech.UUCP (Myke Reynolds) writes:
>[ART's] memory capacity is no less than that of a linear filter, 
>and its size is
>not limited, unlike BP. Since size = memory capacity, its memory capacity
>is limited only by your implementation of a linear equation solver.

I am not familiar with ART, but I am familiar with back-propagation from
the Rummelhart & McClelland PDP volumes, and I don't remember ever
seeing anything about a size limit to networks implemented with back-
propagation.  Could you elaborate?

I am currently working on implementing a simulation for feedforword
networks using BP as a learning rule that should work for arbitrarily
large networks (limited by computer resources, of course).  Since the
equations involved are recursively defined, I don't see why there should
be a size limit on the net.

Zach Frey

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