Path: utzoo!attcan!uunet!lll-winken!lll-tis!ames!mailrus!wasatch!sunset.utah.edu!u-jmolse
From: u-jmolse%sunset.utah.edu@wasatch.UUCP (John M. Olsen)
Newsgroups: comp.ai.neural-nets
Subject: Binary Back Prop question
Message-ID: <799@wasatch.UUCP>
Date: 15 Dec 88 18:04:53 GMT
Sender: news@wasatch.UUCP
Reply-To: u-jmolse%sunset.utah.edu.UUCP@wasatch.UUCP (John M. Olsen)
Organization: University of Utah, Computer Science Dept.
Lines: 19


I'm designing some software, and would like to know if this sort of thing
has been done before.  I'm using a 64 X 64 array of binary inputs, starting
with about 5 levels (each 64 X 64) and the output the same size.  Each node
has 9 inputs, each with a bias to pass or invert the binary value of the
source node, resulting in summations in the set (-9, -7, -5, -3, -1, 1, 3, 
5, 7, 9) where positive results generate a value of 1, and negative values
generate zero.

1.  Is this a brain-dead way of doing things?
2.  Will it be good for anything?  I was thinking in terms of image filters.

The reason I want to do this, is that once it's out of learn mode, I will
probably be able to process about 50,000 to 150,000 of these binary nodes
per second on my home PC (Amiga) by using one of it's custom chips.

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