neuron-request@HPLMS2.HPL.HP.COM ("Neuron-Digest Moderator Peter Marvit") (05/21/91)
Neuron Digest Monday, 20 May 1991
Volume 7 : Issue 28
Today's Topics:
Studentship available
Lisp Code for Recurrent Cascade-Correlation
supervised ART model
RE: Neuron Digest V7 #25
New Graphics for MITRE Neural Network Simulator
Job opportunity at Sydney
Neural nets are universal computing devices
Request for preprints
Send submissions, questions, address maintenance and requests for old issues to
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Use "ftp" to get old issues from hplpm.hpl.hp.com (15.255.176.205).
------------------------------------------------------------
Subject: Studentship available
From: R D Boyle <roger@dcs.leeds.ac.uk>
Date: Mon, 13 May 91 09:04:57 +0100
University of Leeds
Centre for Nonlinear Studies
Studentship
A Cognitive Science/HCI Initiative studentship, to be held
through the Department of Physiology, is available on:
The formation and maintainance of auditory space maps
by neuronal networks.
to be supervised by A.V.Holden & D.Withington (Physiology),
J.E.Rubio & J.Brindley (Applied Mathematical Studies), and
R.Boyle (School of Computer Studies/Artificial Intelligence
Division).
The student will receive an interdisciplinary training in
the Department of Applied Mathematical Studies, School of
Computer Studies, and Department of Physiology. Within the
Department of Physiology there is a Cognitive Science/HCI
funded research project on Synchronisation in neural
netwarks and attention: approaches using synchronous con-
current algorithms, and a SERC Mathematical Biology Student
working on neural networks. The student will review models
of simple topological maps (eg retinotopic maps of ver-
tebrates) and computational maps (mammalian auditory space
maps, where time and intensity information from the 1-D
cochlear is used to map sound sources in 3-D space), and
models for their development. Simulations of biologically
plausible neural networks will used to model electrophysio-
logical data, and to evaluate novel methods for processing
electrophysiological signals. This background will be used
to design models based on continuous state computing modules
(model neurones) for the development and maintainance of
auditory space maps.
Applicants should have a good honours degree in applied
mathematics, computer science,or theoretical physics, with a
strong interest in nonlinear dynamics, cognitive science or
neural networks; or a good training in one of the neurosci-
ences with evidence of mathematical aptitude and a strong
interest in cognitive and computational neuroscience.
For further information contact Dr Arun Holden, Centre for
Nonlinear Studies, The University, Leeds LS2 9JT, tel: 0532
334251, fax 0532 334381 (mark for attention of Dr Holden,
Physiology). E-mail phs6avh @ leeds.cms1
------------------------------
Subject: Lisp Code for Recurrent Cascade-Correlation
From: Scott.Fahlman@SEF1.SLISP.CS.CMU.EDU
Date: Mon, 13 May 91 13:58:25 -0400
Simulation code for the Recurrent Cascade-Correlation (RCC) algorithm is
now available for FTP via Internet. For now, only a Common Lisp version
is available. This is the same version I've been using for my own
experiments, except that a lot of non-portable display and user-interface
code has been removed.
It shouldn't be too hard to modify Scott Crowder's C-based simulator for
Cascade-Correlation to implement the new algorithm, but the likely
"volunteers" to do the conversion are all too busy right now. I'll send
a follow-up notice whenever a C version becomes available.
Instructions for obtaining the code via Internet FTP are included at the
end of this message. If people can't get it by FTP, contact me by E-mail
and I'll try once to mail it to you. If it bounces or your mailer
rejects such a large message, I don't have time to try a lot of other
delivery methods. We are not prepared to distribute the software by
floppy disk or tape -- don't ask.
I am maintaining an E-mail list of people using any of our simulators so
that I can notify them of any changes or problems that occur. I would
appreciate hearing about any interesting applications of this code, and
will try to help with any problems people run into. Of course, if the
code is incorporated into any products or larger systems, I would
appreciate an acknowledgement of where it came from.
NOTE: This code code is in the public domain. It is distributed without
charge on an "as is" basis. There is no warranty of any kind by the
authors or by Carnegie-Mellon University.
There are several other programs in the "code" directory mentioned below:
Cascade-Correlation in Common Lisp and C, Quickprop in Common Lisp and C,
the Migraine/Aspirin simulator from MITRE, and some simulation code
written by Tony Robinson for the vowel benchmark he contributed to the
benchmark collection.
-- Scott
***************************************************************************
For people (at CMU, MIT, and soon some other places) with access to the
Andrew File System (AFS), you can access the files directly from
directory "/afs/cs.cmu.edu/project/connect/code". This file system uses
the same syntactic conventions as BSD Unix: case sensitive names, slashes
for subdirectories, no version numbers, etc. The protection scheme is a
bit different, but that shouldn't matter to people just trying to read
these files.
For people accessing these files via FTP:
1. Create an FTP connection from wherever you are to machine
"pt.cs.cmu.edu". The internet address of this machine is
128.2.254.155, for those who need it.
2. Log in as user "anonymous" with no password. You may see an error
message that says "filenames may not have /.. in them" or something
like that. Just ignore it.
3. Change remote directory to "/afs/cs/project/connect/code". Any
subdirectories of this one should also be accessible. Parent
directories may not be.
4. At this point FTP should be able to get a listing of files in this
directory and fetch the ones you want. The RCC simulator lives in
file "rcc1.lisp".
If you try to access this directory by FTP and have trouble, please
contact me.
The exact FTP commands you use to change directories, list files, etc.,
will vary from one version of FTP to another.
------------------------------
Subject: supervised ART model
From: reynolds@park.bu.edu (John Reynolds)
Date: Mon, 13 May 91 15:43:13 -0400
The following note appeared in Volume 7, Issue 15 of Neuron-Digest:
>Subject: looking for references
>From: <GANKW%NUSDISCS.BITNET@CUNYVM.CUNY.EDU>
>Date: Mon, 25 Mar 91 16:37:00 -0800
>I am looking for articles on the application of ART in supervised
==========
>learning situations. Can anyone help?
>Thanks.
>Kok Wee Gan
>Department of Information Systems and Computer Science
>National University of Singapore
>bitnet address: gankw@nusdiscs.bitnet
>[[Editor's Note: Perhaps someone from Boston U. could answer in a future
>Digest? I thought ART was, strictly speaking, unsupervised only. -PM]]
Gail Carpenter, Stephen Grossberg and I have recently introduced a
supervised ART system called ARTMAP, that autonomously learns to classify
arbitrarily many, arbitrarily ordered vectors in to recognition
categories based on predictive success. Tested on a benchmark machine
learning database in both on-line and off-line simulations, the ARTMAP
system learns orders of magnitude more quickly, efficiently, and
accurately than alternative algorithms. It achieves these properties by
using an internal controller that conjointly maximizes predictive
generalization and minimizes predictive error by linking predictive
success to category size on a trial-by-trial basis, using only local
operations.
It was presented last week at the Wang Institute Conference on Neural
Networks for Vision and Image Processing, and it will also appear at the
upcoming IJCNN meeting (Lecture, Friday, July 12, Session 2, 9:10 -
9:30AM). It will be discussed in an upcoming issue of Neural Networks
(Neural Networks, 4, in press), and it is now available as Technical
Report CAS/CNS-TR-91-001.
Write to the following address:
Boston University Center for Adaptive Systems
and Cognitive and Neural Systems Department
111 Cummington Street, Rm. 244
Boston, MA 02215
or contact Cindy Suchta (cindy@park.bu.edu) to request a copy of the
technical report.
-John
------------------------------
Subject: RE: Neuron Digest V7 #25
From: avlab::mrgate::"a1::raethpg"%avlab.dnet@wrdc.af.mil
Date: Mon, 13 May 91 16:45:39 -0400
From: NAME: Major Peter G. Raeth
FUNC: WRDC/AAWP-1
TEL: AV-785 513-255-7854 <RAETHPG AT A1 AT AVLAB>
To: NAME: VMSMail User "neuron <"neuron@hplpm.hpl.hp.com"@LABDDN@MRGATE>
Re: Information on neural nets in military systems.
Some of this material appears in the USA's National Technical Information
Service. This material is publically accessible. A literature search
could prove very helpful.
------------------------------
Subject: New Graphics for MITRE Neural Network Simulator
From: Russell Leighton <russ@oceanus.mitre.org>
Date: Tue, 14 May 91 13:07:36 -0400
Attention users of the MITRE Neural Network Simulator
Aspirin/MIGRAINES Version 4.0
Version 5.0 of Aspirin/MIGRAINES is targeted for public distribution in
late summer. This will include a graphic interface which will support
X11, SunView, GL and NextStep. We are able to have such an interface
because we are using the libraries of a scientific visualization software
package called apE. Users interested in having this graphical interface
should get a copy of apE2.1 **NOW** so that when Aspirin/MIGRAINES
version 5.0 is released it can be used with the apE software.
The apE software is available from the Ohio Supercomputing Center for a
nominal charge (I believe it is now free for educational institutions,
but I am not sure). Order forms can be ftp'd from "apE.osgp.osc.edu"
(128.146.18.18) in the /pub/doc/info directory.
The Good News:
1. The apE software is free (or nearly free).
2. The apE software is a very portable package.
3. The apE software supports many window systems.
4. You get source with the apE software.
5. The apE tool called "wrench" allows graphical
programmimg, of a sort, by connecting boxes with
data pipes. A neural network compute module
(which A/M can automatically generate) can be
used in these pipelines with other compute/graphics
modules for pre/post processing.
6. We can get out of the computer graphics business.
7. Sexy data displays.
8. ApE is a nice visualization package, and the price
is right.
The Bad News:
1. You need more software than what comes with
the Aspirin/MIGRAINES distribution (although,
you can run without any graphics with the
supplied software).
2. The apE software is not very fast and uses alot
of memory.
3. apE2.1 is a big distribution
Other features to expect in version 5.0:
1. Support for more platforms:
Sun,SGI,DecStation,IBM RS/6000,Cray,Convex,Meiko,i860 based
coprocessors,...
2. New features for Aspirin:
- Quadratic connections (allows hyper-elliptical decision surfaces)
- Auto-Regressive Nodes (allows each node to have an auto-regressive
memory, with tunable feedback weights).
- New file formats
Russell Leighton
INTERNET: russ@dash.mitre.org
Russell Leighton
MITRE Signal Processing Lab
7525 Colshire Dr.
McLean, Va. 22102
USA
------------------------------
Subject: Job opportunity at Sydney
From: Bill Gibson <gibson_w@maths.su.oz.au>
Date: Wed, 15 May 91 22:58:03 +0600
We are currently advertising to fill a lectureship in the School of
Mathematics and Statistics at the University of Sydney, in Australia. I
am a member of a small group of researchers, which includes an
experimental neurobiologist, which is working on biological applications
of neural networks, with a particular interest in the hippocampus. The
School is keen to expand further into the general area of mathematical
biology, and this is an opportunity for someone with these interests to
obtain a tenurable position. The text of the advertisement follows - I
will be happy to provide further information on request. Bill Gibson
LECTURER Ref. 17/04
School of Mathematics and Statistics
The School has active research groups in pure mathematics (algebra,
algebraic geometry, analysis, category theory, group theory), applied
mathematics (mathematical modelling in various areas of biology, finance,
earth sciences and solar astrophysics) and mathematical statistics
(probability, theoretical and applied statistics, neurobiological
modelling). Courses in mathematics are given at all undergraduate and
postgraduate levels and include computer-based courses. Both research
and teaching are supported by a large network of Apollo workstations,
including several high performance processors and colour graphics
systems.
The appointee will have a strong research record in a field related to
nonlinear systems and be prepared to teach courses at all levels,
including computer-based courses. Research areas such as mathematical
biology, neural networks, nonlinear waves and chaos are of particular
interest. Appointments to lectureships have the potential to lead to
tenure and are usually probationary for three years.
Salary: $A33 163 - $A43 096 p.a.
Closing: 4 July 1991
------------------------------
Subject: Neural nets are universal computing devices
From: sontag@control.RUTGERS.EDU
Date: Wed, 15 May 91 13:04:59 -0400
NEURAL NETS ARE UNIVERSAL COMPUTING DEVICES -- request for comments
We have proved that it is possible to build a recurrent net that
simulates a universal Turing machine. We do not use high-order
connections, nor do we require an unbounded number of neurons or an
"external" memory such as a stack or a tape. The net is of the standard
type, with linear interconnections and about 10^6 neurons.
There was some discussion in this medium, some time ago, about questions
of universality. At that time, besides classical references, mention was
made of work by Pollack, Franklin/Garzon, Hartley/Szu, and Sun. It would
appear that our conclusion is not contained in any of the above (which
assume high-order connections or potentially infinitely many neurons).
[More precisely: a ``net'' is as an interconnection of N synchronously
evolving processors, each of which updates its state, a rational number,
according to x(t+1) = s(...), where the expression inside is a linear
combination (with biases) of the previous states of all processors. An
"output processor" signals when the net has completed its computation by
outputting a "1". The initial data, a natural number, is encoded via a
fractional unary representation into the first processor; when the
computation is completed, this same processor has encoded in it the
result of the computation. (An alternative, which would give an entirely
equivalent result, would be to define read-in and read-out maps.) As
activation function we pick the simplest possible "sigmoid," namely the
saturated-linear function s(x)=x if x is in [0,1], s(x)=0 for x<0, and
s(x)=1 for x>1.]
We would appreciate all comments/flames/etc about the technical result.
(Philosophical discussions about the implications of these types of
results have been extensively covered in previous postings.)
A technical report is in preparation, and will be posted to
connectionists when publicly available. Any extra references that we
should be aware of, please let us know.
Thanks a lot,
Hava Siegelman and Eduardo Sontag,
Depts of Comp Sci and Math, Rutgers University.
------------------------------
Subject: Request for preprints
From: Andy Harp <"SRUC::HARP%hermes.mod.uk"@RELAY.MOD.UK>
Date: Fri, 17 May 91 10:19:00 +0000
I am very interested in the following papers that were presented at the
IEEE Symposium on Computer Based Medical Systems. If anyone could mail me
preprints of these papers or knows the e-mail addresses of the authors, I
would be grateful,
Thanks in advance,
Andy Harp.
On-Line Detection of Epileptic Spikes using a Patient-Independent Neural
Network - K. Wilson et al.
Multilevel Neural Network System for EEG Spike Detection - O. Ozdamar et
al.
Detection of the EEG K-Complex Wave with Neural Networks - I. N. Bankman
et al.
From: Andrew Harp
Of: Speech Research Unit
Defence Research Agency
Electronics Division
RSRE
St. Andrews Road
Malvern
Worcs WR14 3PS
England
e-mail: aharp@hermes.mod.uk
------------------------------
End of Neuron Digest [Volume 7 Issue 28]
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