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Neuron Digest Volume 06 Number 21
Neuron Digest Friday, 16 Mar 1990 Volume 6 : Issue 21
Today's Topics:
re: Searle questions
Re: Music by Kohonen's NN
NN's and Music, and a Question (was Music by Kohonen's NN)
Re: NN's and Music, and a Question (was Music by Kohonen's NN)
Neural Networks application?
Applications of Neural Nets in Image Processing and Biomedical Imaging
Re^2: ARTS
TR available - higher order recurrent networks
POSTDOCTORAL POSITION IN COGNITIVE NEUROSCIENCE -- SAN DIEGO
Australian neural networks conference, Feb 1991
NN Conference April 12-13-14
research position available
International Journal of Neural Systems
Send submissions, questions, address maintenance and requests for old issues to
"neuron-request@hplabs.hp.com" or "{any backbone,uunet}!hplabs!neuron-request"
Use "ftp" to get old issues from hplpm.hpl.hp.com (15.255.176.205).
------------------------------------------------------------
Subject: re: Searle questions
From: dank@moc.Jpl.Nasa.Gov (Dan Kegel)
Date: Mon, 12 Mar 90 19:42:42 -0800
I suspect that Searle's Chinese Room claim is just a consequence of
a more basic premise, which can be rephrased:
"Mind you, I'm not saying that computers can't think. It's
computers that are based on pure symbol manipulation that I claim
cannot think. Specifically, they cannot think because they do
not duplicate the causal powers of brains."
Even a computer running an exact simulation of a brain does not satisfy him.
As has been pointed out, it is possible in principle to graft biological
sensory organs [aka causal powers] onto such a computer. Searle would,
if pressed, probably admit that the resulting system could think and
understand. After all, it has duplicated a brain's causal powers, hasn't
it? {Can somebody supply Searle's address, so we can direct the question
to him?}
But are sensory inputs really needed for thought? Imagine disconnecting
a brain's "causal powers" one by one. Does thinking cease when the nose
is disconnected? No. When the eyes are shut? No. When the angiotensin
receptors that mediate thirst are removed? No again; in fact, it seems
reasonable that thought could continue when all sensory input is removed.
The remaining causal power is memory, which I state is sufficient.
Dan Kegel
[[ Editor's Note: John Searle's address is searle@cogsci.berkeley.edu. -PM ]]
------------------------------
Subject: Re: Music by Kohonen's NN
From: smoliar@vaxa.isi.edu (Stephen Smoliar)
Organization: USC-Information Sciences Institute
Date: 13 Mar 90 18:34:30 +0000
[[ From last issue: ]]
>Kohonen's "Neural Network Music" actually is not Neural Network Music
>(at least what he presented at IJCNN '90) He informed the audience
>that it was based more on a stochastic analysis of human composers
>(including mixing various composers).
Readers more interested in what can be done with neural networks may wish
to check out Peter Todd's contribution to the 1988 Connectionist Models
Summer School. Todd is a psychologist, and he seems more concerned with
modeling phenomena which have been observed in psychological experiments.
I would say there is still some doubt as to how relevant those
experiments are to music as it is actually practiced, but at least Todd
appears to be approaching the problem more scientifically.
=========================================================================
USPS: Stephen Smoliar
USC Information Sciences Institute
4676 Admiralty Way Suite 1001
Marina del Rey, California 90292-6695
Internet: smoliar@vaxa.isi.edu
"Only a schoolteacher innocent of how literature is made could have written
such a line."--Gore Vidal
------------------------------
Subject: NN's and Music, and a Question (was Music by Kohonen's NN)
From: robert@aerospace.aero.org (Bob Statsinger)
Organization: Ahh...wouldntya like to know!
Date: 14 Mar 90 18:51:22 +0000
The two most recent issues (vols 12 and 13) of "Computer Music
Journal" are completely devoted to neural nets and connectionism as
applied to musical composition and models of music perception. Todd has a
GREAT article in vol 13 on a recurrent network he developed for
algorithmic composition. There are also backpropagation models of pitch
perception (Jenkins), bidirectional linear nets for inferring tonality
(Bharucha), and in vol 12 an ART system for musical classification.
This semester I am working on applying invariant object
recognition to attempt to model the recognition of musical melody
independent of key signature (invariance with respect to tempo and mild
distortion invariance are also desirable). I have not seen this attempted
anywhere in the literature that I've seen so far. If anyone has seen such
an attempt, PLEASE respond in a followup posting and/or by e-mail. Thanx
much.
Bob Statsinger Robert@aerospace.aero.org
The employers expressed herein are strictly mine and are
not necessarily those of my opinion's....uh..er...whatever...
------------------------------
Subject: Re: NN's and Music, and a Question (was Music by Kohonen's NN)
From: smoliar@vaxa.isi.edu (Stephen Smoliar)
Organization: USC-Information Sciences Institute
Date: 15 Mar 90 21:47:01 +0000
> The two most recent issues (vols 12 and 13) of "Computer Music
>Journal" are completely devoted to neural nets and connectionism as
>applied to musical composition and models of music perception.
Thanks for coming to my rescue, Bob! I received two electronic mail
requests for details but was tardy in responding due to being snowed
under by two papers I'm trying to wrap up! Nevertheless, your citation
had better get corrected before things get out of hand. The two issues
are Numbers 3 and 4 of Volume 13 (not volumes 12 and 13). For those
interested in the specific articles, the Jenkins piece on pitch
perception and Gjerdingen's ART piece are in Number 3. Bharucha and Todd
are in Number 4. Personally, I did not think very much about the ART
article; but I am prepared to be persuaded otherwise.
=========================================================================
USPS: Stephen Smoliar
USC Information Sciences Institute
4676 Admiralty Way Suite 1001
Marina del Rey, California 90292-6695
Internet: smoliar@vaxa.isi.edu
"Only a schoolteacher innocent of how literature is made could have written
such a line."--Gore Vidal
------------------------------
Subject: Neural Networks application?
From: Javier Tuya Gonzalez <Tuya@etsiig.uniovi.es>
Date: 16 Mar 90 16:50:00 +0200
Has anybody information (people who works in, papers published, etc.)
about some application of Neural Networks for:
Classification of crystal structures using X-ray diffraction data
Could be possible to apply Neural Networks for it?
Please, post me E-mail if you can help me.
Thanks in advance.
+--------------------------------------+------------------------------------+
| Pablo Javier Tuya Gonzalez | PSI: PSI%(02145)285060338::TUYA |
| E.T.S. Ingenieros Industriales | E-Mail: tuya@etsiig.uniovi.es |
| Area de Lenguajes y Sistemas | HEPNET: tuya@16515.decnet.cern.ch |
| Informaticos (Universidad de Oviedo) | : EASTVC::TUYA (16.131) |
| Carretera de Castiello s/n. | Phone: (..34-85) 338380 ext 278 |
| E-33394 GIJON/SPAIN | FAX: (..34-85) 338538 |
+--------------------------------------+------------------------------------+
------------------------------
Subject: Applications of Neural Nets in Image Processing and Biomedical Imaging
From: m20163@mwvm.mitre.org (Nahum Gershon)
Date: Fri, 16 Mar 90 09:52:10 -0500
I am looking for information on any work done on the use of neural nets in
image processing and also in biomedical imaging. Any help would be greatly
appreciated.
Nahum Gershon
The MITRE Corp.
MS Z575
7525 Colshire Drive
McLean, VA 22102
E-mail: gershon@mitre.org
Phone: (703) 883-7518
Fax: (703) 883-7175
------------------------------
Subject: Re^2: ARTS
From: gaudiano@bucasb.bu.edu
Date: Thu, 15 Mar 90 15:00:20 -0500
>>>> In reply to Jason Kingdon's message about the problem with ART1:
Well, there are two ways to address you question: one answer is that,
indeed, you have found one of the problems with ART1. This problem has to
do with the fact that all top-down LTM traces are forced to 1 in fast
learning (or asymptotically in slow learning), so that the top-down
template match exceeds the critical strength regardless of the number of
nonzero weights in the top-down LTM trace. This can in fact be avoided in
ART2-3.
The other answer: The ART1 architecture was designed so that templates
can only shrink. This ensures that a maximal number of exemplars can be
categorized, depending on the vigilance level. If a single node has
non-zero strength, then at vigilance 1 you can only code the one-element
vector, but as you drop vigilance you can code more and more patterns
based on the "atomic" subpattern.
So basically you have shown that this categorization network, when
severely restricted in memory capacity, and when forced to make extremely
fine discriminations (vigilance=1) will only become stable on the most
*basic* pattern that can possibly grab a category (but can still code
supersets at lower vigilance).
Does this constitute an example of "rendering the system useless"?
I would consider it a fascinating feature.
Paolo Gaudiano
------------------------------
Subject: TR available - higher order recurrent networks
From: "Giles L." <giles@fuzzy.nec.com>
Date: Fri, 09 Mar 90 15:11:50 -0500
This 8-page paper will appear in Advances in Neural Information
Processing Systems 2, D.S. Touretzky (ed), Morgan Kaufmann, San Mateo,
Ca., 1990.
HIGHER ORDER RECURRENT NETWORKS & GRAMMATICAL INFERENCE
C. L. Giles*, G. Z. Sun, H. H. Chen, Y. C. Lee, D. Chen Department of
Physics and Astronomy and Institute for Advanced Computer Studies,
University of Maryland, College Park, MD 20742. *NEC Research Institute,
4 Independence Way, Princeton, N.J. 08540
ABSTRACT
We design a higher-order single layer, recursive neural network which
easily learns to simulate a deterministic finite state machine and infer
simple regular grammars from small training sets. An enhanced version of
this neural network state machine is then constructed and connected
through a common error term to an external analog stack memory. The
resulting hybrid machine can be interpreted as a type of neural net
pushdown automata. The neural net finite state machine part is given the
primitives, push and pop, and is able to read the top of the stack.
Using a gradient descent learning rule derived from a common error
function, the hybrid network learns to effectively use the stack actions
to manipulate the stack memory and to learn simple context-free grammars.
If the neural net pushdown automata are reduced through a heuristic
clustering of neuron states and actions, the neural network reduces to
correct pushdown automata which recognize the learned context-free
grammars.
For a hard copy of the above, please send a request to:
gloria@research.nec.com or
Gloria Behrens
NEC Research Institute
4 Independence Way
Princeton, N.J. 08540
------------------------------
Subject: POSTDOCTORAL POSITION IN COGNITIVE NEUROSCIENCE -- SAN DIEGO
From: trejo@nprdc.arpa (Leonard J. Trejo)
Organization: Navy Personnel R & D Center
Date: 13 Mar 90 22:42:49 +0000
POSTDOCTORAL POSITION IN COGNITIVE NEUROSCIENCE -- SUMMER/FALL 1990
The Neurosciences Division of the Navy Personnel Research and
Development Center (NPRDC), San Diego, is looking for a recent Ph. D.
to study electrophysiological correlates of human cognition. Ongoing
research includes neuroelectric (EEG and ERP) and neuromagnetic
(evoked field) technology. The primary emphasis is on the improvement
of on-job performance prediction and training; however, considerable
emphasis is given to basic research issues. Another area of interest
is in real-time electrophysiological signal processing using adaptive
filters and neural networks. The well-equipped Neuroscience Labora-
tory includes two Concurrent computer systems, several '386 PC sys-
tems, a Macintosh SE, and other equipment, as well as extensive
stimulus presentation, data acquisition and analysis software. Access
privileges to VAX 11/780, IBM 4341, and SUN 4 systems, and the INTER-
NET network are also available. An associate investigator role will be
assumed by the successful candidate and he/she will be expected to
develop a line of research in concert with Center goals.
Qualifications include:
1. U. S. Citizenship
2. Ph. D., Sc. D., or equivalent in psychology or neuroscience
received not more than 7 years from date of award
Additional experience desired:
1. Cognitive psychophysiology training / experience
2. Experimental design / methodology
3. Multivariate / univariate statistics
4. Proficiency with UNIX and C programming
The position is available through the Postdoctoral Fellowship
Program funded by the U.S. Navy Office of Naval Technology (ONT) and
administered by the American Society for Engineering Education (ASEE).
Duration of the appointment is for one year, and may be renewed for up
to two additional years. Stipends range from $34,000 to $38,000 per
annum depending upon experience. A relocation allowance may be nego-
tiated; the amount is based on the personal situation of the partici-
pant. Funds will be available for limited professional travel.
NPRDC is located on top of Pt. Loma, overlooking San Diego Harbor
and downtown San Diego. Reasonably priced rental housing is available
in within a 5-mile radius of the Center. San Diego offers an excel-
lent climate and environment as well as a wide range of academic, mil-
itary, and industrial research institutions.
The application deadlines are April 1, 1990, for terms beginning
in the summer, and July 1, 1990, for terms beginning in the fall. For
information about the ONT Postdoctoral Fellowship Program and an
application form, please contact:
American Society for Engineering Education
Projects Office, Attention: Bob Davis
11 Dupont Circle, Suite 200
Washington, DC 20036
(202) 293-7080
For information about the NPRDC Neurosciences Division, contact:
Dr. Leonard J. Trejo
Neuroscience Division, Code 141
Navy Personnel Research and Development Center
San Diego, CA 92152-6800
(619) 553-7711
INTERNET: trejo@nprdc.navy.mil UUCP: ucsd!nprdc!trejo
============================================================================
USENET : trejo@nprdc.navy.mil UUCP: ucsd!nprdc!trejo
U.S. Mail: Leonard J. Trejo, Ph. D. Phone: (619) 553-7711
Neurosciences Division (AV) 553-7711
NPRDC, Code 141
San Diego, CA 92152-6800
------------------------------
Subject: Australian neural networks conference, Feb 1991
From: Janet Wiles <janet@psych.psy.uq.OZ.AU>
Date: Wed, 14 Mar 90 16:56:21 +1100
PRELIMINARY ANNOUNCEMENT
SECOND AUSTRALIAN CONFERENCE ON NEURAL NETWORKS
(ACNN'91)
4th - 6th February 1991
THE UNIVERSITY OF SYDNEY
SYDNEY, AUSTRALIA
The second Australian conference on neural networks will be held in
Sydney on Feb 4, 5 and 6, 1991, at the Stephen Roberts Theatre, The
University of Sydney. This conference is interdisciplinary, with
emphasis on cross discipline communication between Neuroscientists,
Engineers, Computer Scientists, Mathematicians and Psychologists
concerned with understanding the integrative nature of the nervous system
and its implementation in hardware/software.
Neuroscientists concerned with understanding the integrative function of
neural networks in vision, audition, motor, somatosensory and autonomic
functions are invited to participate and learn how modelling these
systems can be used to sharpen the design of experiments as well as to
interpret data.
Mathematicians and computer scientists concerned with the various new
neural network algorithms that have recently become available, as well as
with statistical thermodynamic approaches to network modelling and
simulation are also invited to contribute.
Engineers concerned with the advantages which parallel and distributed
computing architectures offer in the solution of various classes of
problems and with the state of the art techniques in the hardware
implementation of neural network systems are also invited to participate.
Psychologists interested in computational models of cognition and
perception are invited to contribute and to learn about neural network
techniques and their biological and hardware implementations.
ACNN'91 will feature invited keynote speakers in the areas of
neuroscience, learning, modelling and implementations. The program will
include pre-conference workshops, presentations and poster sessions.
Proceedings will be printed and distributed to the attendees.
Expression of Interest:
-----------------------
Please fill the expression of interest form below and return it to
Miss Justine Doherty at the address below.
___ I wish to attend the conference
___ I wish to attend the workshops
___ I wish to present a paper
Title: _____________________________________________________
_____________________________________________________
Authors: ___________________________________________________
_____________________________________________________
___ I wish to be on your mailing list
My areas of interests are:
____ Neuroscience ____ Learning ____ Modelling ____ Implementation
____ Applications ____ Other: _______________________________________
First Name: ___________________________
Surname: ______________________________
Title: ________________________________
Position:______________________________
Department: ___________________________________________________________
Institution:___________________________________________________________
Address:_______________________________________________________________
_______________________________________________________________________
City: _______________________________ State: __________________________
Zip Code: _________________________ Country: __________________________
Tel: ______________________________ Fax: ______________________________
Email: _________________________________________
________________________________________________________________________
Organising committee:
Chairman Dr Marwan Jabri, Sydney
Co-chairman Professor Max Bennett, Sydney
Technical Program Chairman Dr Ah Chung Tsoi, ADFA
Technical Program Co-Chairman Professor Bill Levick, ANU
Publicity Dr Janet Wiles, Queensland
Registration Electrical Engineering Foundation
Conference Committee Professor Yanni Attikiousel, WA
Professor Max Bennett, Sydney
Professor Bob Bogner, Adelaide
Professor Richard Brent, ANU
Dr Jacob Cybulski, TRL
Dr Marwan Jabri, Sydney
Professor Bill Levick, ANU
Dr Tom Osbourn, UTS
Professor Steve Redman, ANU
Ass/Prof Sam Reisenfeld, OTC Ltd
Professor Graham Rigby, UNSW
Professor Steve Schwartz, Queensland
Dr Ah Chung Tsoi, ADFA
Dr Charles Watson, DSTO
Dr Janet Wiles, Queensland
Dr Hong Yan, Sydney
For further information contact:
Miss Justine Doherty
Secretariat ACNN'91
Sydney University Electrical Engineering
NSW 2006 Australia
Tel: (+61-2) 692 3659
Fax: (+61-2) 692 3847
Email: acnn91@ee.su.oz.au
_____________________________________________________________________________
------------------------------
Subject: NN Conference April 12-13-14
From: Samir Sayegh <sayegh@ed.ecn.purdue.edu>
Date: Thu, 15 Mar 90 17:41:16 -0500
Third Conference on Neural Networks and PDP (Robotics and Vision)
Indiana-Purdue University
Deadline for submission of a 1 page abstract is March 23. e-mail and FAX
submissions OK. Conference fee is $25. Students attend free.
Inquiries and abstracts:
S.Sayegh
Physics Dept.
Indiana Purdue University
Ft Wayne In 46805
email: sayegh@ed.ecn.purdue.edu
sayegh@ipfwcvax.bitnet
fax: (219) 481-6800
voice:(219)481-6157
------------------------------
Subject: research position available
From: "James A. Reggia" <reggia@cs.UMD.EDU>
Date: Thu, 15 Mar 90 20:22:20 -0500
RESEARCH SCIENTIST POSITION AVAILABLE IN NEURAL MODELLING
The component of The Food and Drug Administration responsible for
regulating medical devices has an opening for a research scientist. This
is a permanent civil service position available for someone interested in
modelling the neural activity of the hippocampus. The candidate will
focus his/her research on improving the safety and effectiveness of
electro-convulsive therapy devices. The candidate must have a PhD in one
of the physical sciences. Any additional training in the biological
sciences is highly desirable. For more information call or write to:
Dr. C. L. Christman
(301) 443-3840
Address:
FDA
HFZ-133
12721 Twinbrook Pkwy
Rockville, MD 20857
(Do NOT send inquiries for further information via email to the
individual posting this announcement.)
------------------------------
Subject: International Journal of Neural Systems
From: Benny Lautrup <LAUTRUP%nbivax.nbi.dk@CUNYVM.CUNY.EDU>
Date: Fri, 16 Mar 90 12:28:00 +0100
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
The International Journal of Neural Systems is a quarterly journal
which covers information processing in natural and artificial neural
systems. It publishes original contributions on all aspects of this
broad subject which involves physics, biology, psychology, computer
science and engineering. Contributions include research papers, reviews
and short communications. The journal presents a fresh undogmatic
attitude towards this multidisciplinary field with the aim to be a
forum for novel ideas and improved understanding of collective and
cooperative phenomena with computational capabilities.
ISSN: 0129-0657 (IJNS)
- ----------------------------------
Contents of issue 1:
1. C. Peterson and B. Soderberg: A new Method for mapping Optimization
Problems onto Neural Networks.
2. M. G. Paulin, M. E. Nelson and J. M. Bower: Dynamics of Compensatory
Eye Movement Control: An Optimal Estimation Analysis of the
Vestibulo-Ocular Reflex.
3. P. Peretto: Learning Learning Sets in Neural Networks.
4. B. A. Huberman: The Collective Brain.
5. S. Patarnello and P. Carnevali: A Neural Network Model to Simulate
a conditioning Experiment.
6. J.-P. Nadal: Study of a Growth Algorithm for a Feed-Forward Network.
7. E. Oja: Neural Networks, Principal Components and Subspaces.
8. S. Bacci, G. Mato, and N. Parga: The Organization of Metastable
States in a Neural Network with Hierarchical Patterns.
9. A. Lansner and O. Ekeberg: A One-layer Feedback Artificial Neural
Network with a Bayesian Learning Rule.
10. J. Midtgaard and J. Hounsgaard: Nerve Cells as Source of Time
Scale and Processing Density in Brain Function.
11. S. Chen: On Computational Vision.
- ----------------------------------
Contents of issue 2:
1. P. Baldi and A. Attiya: Oscillations and synchronizations in
neural networks: An exploration of the labeling hypothesis.
2. A. W. Smith and D. Zipser: Learning sequential structure with
the real-time recurrent learning algorithm.
3. M. R. Davenport and G. W. Hoffmann: A recurrent neural network
using tri-state hidden neurons to orthogonalize the memory space.
4. H. K. M. Yusuf, S. Rahman and H. Akhtar:
Rats kept in environmental isolation for twelve months from weaning:
Performance in maze learning and visual discrimination tasks
and brain composition.
5. H. C. Card and W. R. Moore:
VLSI devices and circuits for learning in neural networks.
6. L. Gislen, C. Peterson and B. Soderberg:
"Teachers and classes" with neural networks.
7. A. E. Gunhan, L. P. Csernai, and J. Randrup:
Unsupervised competitive learning in Purkinje networks.
8. H.-U. Bauer and T. Geisel:
Motion detection and direction detection in local neural nets.
- ----------------------------------
Editorial board:
B. Lautrup (Niels Bohr Institute, Denmark) (Editor-in-charge)
S. Brunak (Technical Univ. of Denmark) (Assistant Editor-in-Charge)
D. Stork (Stanford) (Book review editor)
Associate editors:
B. Baird (Berkeley)
D. Ballard (University of Rochester)
E. Baum (NEC Research Institute)
S. Bjornsson (University of Iceland)
J. M. Bower (CalTech)
S. S. Chen (University of North Carolina)
R. Eckmiller (University of Dusseldorf)
J. L. Elman (University of San Diego)
M. V. Feigelman (Landau Institute for Theoretical Physics)
F. Fogelman-Soulie (Paris)
K. Fukushima (Osaka University)
A. Gjedde (Montreal Neurological Institute)
S. Grillner (Nobel Institute for Neurophysiology, Stockholm)
T. Gulliksen (University of Oslo)
D. Hammerstroem (University of Oregon)
J. Hounsgaard (University of Copenhagen)
B. A. Huberman (XEROX PARC)
L. B. Ioffe (Landau Institute for Theoretical Physics)
P. I. M. Johannesma (Katholieke Univ. Nijmegen)
M. Jordan (MIT)
G. Josin (Neural Systems Inc.)
I. Kanter (Princeton University)
J. H. Kaas (Vanderbilt University)
A. Lansner (Royal Institute of Technology, Stockholm)
A. Lapedes (Los Alamos)
B. McWhinney (Carnegie-Mellon University)
M. Mezard (Ecole Normale Superieure, Paris)
A. F. Murray (University of Edinburgh)
J. P. Nadal (Ecole Normale Superieure, Paris)
E. Oja (Lappeenranta University of Technology, Finland)
N. Parga (Centro Atomico Bariloche, Argentina)
S. Patarnello (IBM ECSEC, Italy)
P. Peretto (Centre d'Etudes Nucleaires de Grenoble)
C. Peterson (University of Lund)
K. Plunkett (University of Aarhus)
S. A. Solla (AT&T Bell Labs)
M. A. Virasoro (University of Rome)
D. J. Wallace (University of Edinburgh)
D. Zipser (University of California, San Diego)
- ----------------------------------
CALL FOR PAPERS
Original contributions consistent with the scope of the journal are
welcome. Complete instructions as well as sample copies and subscription
information are available from
The Editorial Secretariat, IJNS
World Scientific Publishing Co. Pte. Ltd.
73, Lynton Mead, Totteridge
London N20 8DH
ENGLAND
Telephone: (44)1-446-2461
or
World Scientific Publishing Co. Inc.
687 Hardwell St.
Teaneck
New Jersey 07666
USA
Telephone: (1)201-837-8858
or
World Scientific Publishing Co. Pte. Ltd.
Farrer Road, P. O. Box 128
SINGAPORE 9128
Telephone (65)278-6188
------------------------------
End of Neuron Digest [Volume 6 Issue 21]
****************************************
