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From: norman@lasspvax.UUCP (Norman Ramsey)
Newsgroups: net.math
Subject: Neural Net COmputing
Message-ID: <663@lasspvax.UUCP>
Date: Mon, 11-Nov-85 19:09:55 EST
Article-I.D.: lasspvax.663
Posted: Mon Nov 11 19:09:55 1985
Date-Received: Wed, 13-Nov-85 07:34:02 EST
Reply-To: norman@lasspvax.UUCP (Norman Ramsey)
Organization: LASSP, Cornell University
Lines: 22
Summary: A model of human memory may lead to some interesting devices


I recently heard a talk given here on Hopfield memories and neural network
devices. The work I heard about is being done at Bell Labs by Larry
Jaeckel's group. The idea is fairly simple: you take N "neurons", connect
each to all the others, and let the firing rate of a given neuron depend on
the stimuli on its inputs, which can be excitatory or inhibitory. Jaeckel's
people are using op amps with resistors and capacitors, where voltage is the
quantity analogous to firing rate, and conductance is analogous to the
transmittivity (or whatever) of a synapse. Apparently they have been able to
make an associative memory out of these gadgets, and have also taken a good
crack at the traveling salesman problem (by letting the device minimize
energy).

Does anyone know more about the mathemtics of these things? How many
elements can be stored in such an associative memory? What are expected
error rates like? What are the possibilities for programming or calculating
with these devices?
-- 
Norman Ramsey

ARPA: norman@lasspvax  -- or --  norman%lasspvax@cu-arpa.cs.cornell.edu
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