neuron-request@HPLMS2.HPL.HP.COM ("Neuron-Digest Moderator Peter Marvit") (01/31/91)
Archive-name: ai/neural-nets/backprop/1991-01-26
Original-posting-by: neuron-request@HPLMS2.HPL.HP.COM ("Neuron-Digest Moderator Peter Marvit")
Original-subject: Neuron Digest V7 #5
Reposted-by: emv@ox.com (Edward Vielmetti)
Neuron Digest Friday, 25 Jan 1991
Volume 7 : Issue 5
Today's Topics: ...
Backprop s/w
[Other topics deleted. --Ed]
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From: Shawn Lockery <shawn@helmholtz.sdsc.edu>
Date: Mon, 14 Jan 91 14:59:54 -0800
Subject: Backprop s/w
Several months ago I asked about canned backprop simulators. At long
last, here is the result of my query:
=======================================-
Barak Pearlmutter has written a dynamical backprop simulator. A version
of his program that solves a toy problem and that is readily modifiable
is available by anonymous ftp from helmholtz.sdsc.edu. The directory is
pub/ and the filename is pearlmutter.tar
=======================================-
Yoshiro Miyata (miyata@dendrite.colorado.edu) has written an excellent
public domain connectionist simulator with a nice X windows or Sun View
interface. It is called SunNet. He provides a pretty easy to learn
"general" definition language so a user can experiment with quite varied
back-prop and non-conventional architectures. Examples are provided of
backpropagation, boltzmann learning, and others. Source code is
available by anonymous ftp from boulder. Look for SunNet5.5.tar.Z at
boulder.colorado.edu.
=======================================-
Yan Le Cun (Department of Computer Science, University of Toronto,
Toronto, Ontario, M5S 1A4, Canado) has written a commercial simulator
called SN /2 that is powerful and well documented.
=======================================
The Rochester Connectionist Simulator (RCS) is obtainable by anonymous
ftp from cs.rochester.edu. You will find the code in the directory
pub/simulator.
========================================
The speech group at Oregon Graduate Institute has written a
conjugate-gradient optimization program called OPT to train fully
connected feed-forward networks. It is available by anonymous ftp from
cse.ogi.edu. The code is in the directory pub/speech. Copy the file
opt.tar. You will need to use the unix "tar" command to process the file
once you have it on your computer.
========================================-
For the Macintosh, there is the commercial program called MacBrain
(Neuronics, Inc., ! Kendall Square #2200, Cambridge, MA 02139). It has
the usual Macintosh bells and whitsles and costs $400.
========================================-
For the Macintosh, there is a public domain program called Mactivation.
Mactivation version 3.3 is available via anonymous ftp on
alumni.Colorado.EDU (internet address 128.138.240.32) The file is in /pub
and is called mactivation.3.3.sit.hqx
Mactivation is an introductory neural network simulator which runs on
all Apple Macintosh computers. A graphical interface provides direct
access to units, connections, and patterns. Basic concepts of network
operations can be explored, with many low level parameters available for
modification. Back-propagation is not supported (coming in 4.0) A user's
manual containing an introduction to connectionist networks and program
documentation is included. The ftp version includes a plain text file and
an MS Word version with nice graphics and footnotes. The program may be
freely copied, including for classroom distribution. for version 4.0.
You can also get a copy by mail. Send $5 to Mike Kranzdorf, Box 1379,
Nederland, C0 80466-1379.
========================================-
For 386 based PC's, you may purchase ExploreNet from HNC, 5501 Oberlin
Drive, San Diego, CA 92121. You don't get source code for your $750, but
it's powerful and flexible.
========================================-
For IBM PC's, there is a disk that comes along with the third volume of
the PDP books (Parallel Distributed Processing, Rumelhart, McClelland and
the PDP Research Group, MIT Press, 1986 . You get lots of source code,
and the third volume itself is a nice manual.
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End of Neuron Digest [Volume 7 Issue 5]
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