Copy Link
Add to Bookmark
Report
Neuron Digest Volume 09 Number 15
Neuron Digest Saturday, 4 Apr 1992 Volume 9 : Issue 15
Today's Topics:
Company Info
Using logistic function with polynomials
Neural networks plus expert systems
Some addresses ...
Academic Programs
Critiques of Neural Darwinism (Request For...)
68 neurosimulators
Send submissions, questions, address maintenance, and requests for old
issues to "neuron-request@cattell.psych.upenn.edu". The ftp archives are
available from cattell.psych.upenn.edu (128.91.2.173). Back issues
requested by mail will eventually be sent, but may take a while.
----------------------------------------------------------------------
Subject: Company Info
From: spers@hydra.atc.com (Suneet Garg)
Date: Sat, 07 Mar 92 17:45:43 -0800
[[ Editor's Note: As long-time subscribers know, I do not publish resumes
or "jobs wanted", though I often post "jobs offered." However, I think
this person's request is of broader interest. I hope anyone who answers
him personally also cc's Neuron Digest. -PM ]]
Hi!.
I am interested in information on companies (commercial) that offer
employment oppurtunities (and therefore do this kind of work) in the
field of neural-nets/machine vision or even more broadly in the field of
AI.
All my attempts to get such infomration from company directories,
libraries etc. have been frustrated because they dont't even mention it
as a sub-field of commercial computer industry. Probably this is because
the field itself is nascent.
Would you guys be knowing of any source of such information, lets say "AI
companies in the state of California". The help I am expecting could be
in any form (the form of tel-no or mail address):
--> A list itself.
--> E-mail address of a source.
--> A Magazine, Newspaper.
--> Commercial Data bank.
Any help is fine.
ThanX
Suneet Garg
Please email to : suneet@ruby.atc.com
------------------------------
Subject: Using logistic function with polynomials
From: pb@kailash.ernet.in (Pushpak Bhattacharya)
Date: Mon, 09 Mar 92 23:23:27 +0700
We find that using the logistic function 1/(1+exp(-x)) it is not possible
to learn polynomials like y=x or y=x**2 or y=x**3 using BP based
feedforward network - the net simply doesn't converge. However functions
like sin(x) or cos(x) can be learnt. It seems infinite series is easier
to learn than finite series using the above logistics.
However using the logistic 1/(1+x) the above polynomials were
learnable by retricting the network to operate in 0-to-1 region where the
new logistic is differentiable. Comments /explanations/suggestions
regarding this observation is most welcome and in fact eagerly sought.
Pushpak Bhattacharyya
IIT Bombay
pb@cse.iitb.ernet.in
or to
Bhaven Avalani
avalani@cse.iitb.ernet.in
------------------------------
Subject: Neural networks plus expert systems
From: fan@sun490.as.edu.tw (fan )
Date: Wed, 11 Mar 92 09:50:31 -0600
[[ Editor's Note: The obvious answer is "YES" but I'm not sure where to
send this person who is obviously just starting out his search. What are
good first papers on the subject (before delving into the technical
complexities)? Are there any survey papers? -PM ]]
Dose anyone have any idea of combining the neural network and the
expert system?
I heard there is some system using the neural network to accept the
signal of sensors and generate a rough pattern to the expert system to
find out the exact pattern.
Does any has any comments about that? Is it possible to combine the
advantages of both the Neural and the Symbolic approaches to generate a
power one?
Fan...
------------------------------
Subject: Some addresses ...
From: KRISH%tifrvax.BITNET@pucc.Princeton.EDU
Date: Mon, 30 Mar 92 23:41:00 +0700
[[ Editor's Note: From an Indian address, this seems like a reasonable
question. -PM ]]
I am looking for the mailing addresses (postal as well as email (if
available)), of the following :
a) Neural Computation Journal
b) NIPS proceedings
I would basically like the addresses of the publishers, as we are
interested in subscribing to these. Could someone help ? Thanks in
advance.
Krish,
Tata Institute of Fundamental Research
Bombay, India
------------------------------
Subject: Academic Programs
From: worth@park.bu.edu (Andrew J. Worth)
Organization: Boston University Center for Adaptive Systems
Date: 30 Mar 92 18:39:17 +0000
As part of ISSNNet's goal of building a data base of academic programs
dealing with the general field of "Neural Networks", we will be
sending a standard form to all academic institutions that we know
about asking for the following information:
- - Official address to contact for more information (surface mail and
email)
- - Official description of the program
- - Names of Faculty Members and their interests
- - Emphasis of the program with regard to the field of Neural Networks
- - Degrees requirements (BA, BS, MA, MS, PhD, etc.)
- - Short description of courses offered
- - Computing resources (Hardware and Software Tools)
- - Number of Students (grad/undergrad) and related faculty
- - Student Contacts (w/ telephone numbers, email and surface addresses,
degree sought, interests, and date of graduation)
Since you are an active ISSNNet member (active meaning you read
this newsgroup) you can help in two ways:
1) by giving us suggestions on any other information that you think
would be appropriate in the data base, and
2) by giving us the surface mail address of the institution to which
you are affiliated.
You can respond to this message or else send email to
issnnet-acad-progs@bucasb.bu.edu
Thank you for your time and effort,
Andy.
- ----------------------------------------------------------------------
Andrew J. Worth (617) 353-6741 ISSNNet, Inc.
ISSNNet Academic Program Editor P.O. Box 15661
issnnet-acad-progs@park.bu.edu Boston, MA 02215 USA
worth@park.bu.edu
- ----------------------------------------------------------------------
------------------------------
Subject: Critiques of Neural Darwinism (Request For...)
From: dhg@scs.carleton.ca (Daryl Herbert Graf)
Organization: School of Computer Science, Carleton University, Ottawa, Canada
Date: 31 Mar 92 00:49:30 +0000
[[ Editor's Note: Although the author asks for reply's to go to him, I
would be interested in starting a discussion in Edelman's work. I find
it very intriguing and though-provoking. I have yet to examine his models
in great detail, but often have a difficult time reading his books since
they seem a bit disorganized; they could use a good editor. What are
*your* thoughts? -PM ]]
I am looking for critical reviews of Gerald Edelman's theory of neuronal
group selection. I have read the nmaterial in the attached bibliography
and I would like to balance this with additional papers, analyses,
observations, or opinions regarding this work from the connectionist, and
neuroscience communities. In order to avoid cluttering the news, I would
ask those who wish to reply to do so directly to me. I will post a
summary in the near future. Many thanks in advance.
Daryl Graf
Study Group on Evolutionary Computing Techniques
School of Computer Science
Carleton University
Ottawa, Ontario, Canada
email: dhg@scs.carleton.ca
Bibliography:
Edelman, G.M. (1987) "Neural Darwinism: the Theory of
Neuronal Group Selection", Basic, NY
Edelman, G.M. (1989) "The Remembered Present: a Biological
Theory of Consciousness", Basic, NY
Edelman, G.M. (1981) Group selection as the basis for higher
brain function. In "The Organization of the Cerebral Cortex",
F.O. Schmitt, F.G. Worden, G. Adelman, S.G. Dennis, eds.,
pp. 535-563, MIT Press, Cambridge, Mass.
Edelman, G.M. (1978) Group selection and phasic re-entrant
signalling: a theory of higher brain function. In "The
Mindful Brain", G.M. Edelman, V.B. Mountcastle, eds.,
pp. 51-100, MIT Press, Cambridge, Mass.
Edelman, G.M., Finkel, L.H. (1984) Neuronal group selection
in the cerebral cortex. In "Dynamic Aspects of Neocortical
Function", G.M. Edelman, W.E. Gall, W.M. Cowan, eds.,
pp. 653-695. Wiley, NY
Edelman, G.M., Reeke, G.N., (1982) Selective networks capable of
representative transformations, limited generalizations,
and associative memory, Proc. Natl. Acad. Sci. USA
79:2091-2095
Finkel, L.H., Edelman, G.M. (1987) Population rules for synapses
in networks. In "Synaptic Function", G.M. Edelman, W.E. Gall,
W.M. Cowan, eds., pp.711-757, Wiley, NY
Finkel, L.H., Edelman, G.M. (1985) Interaction of synaptic
modification rules within populations of neurons, Proc.
Natl. Acad. Sci. USA 82:1291-1295
Reeke, G.N., Finkel, L.H., Sporns, O., G.M. Edelman, (1989)
Synthetic neural modeling: a multilevel approach to the
analysis of brain complexity. In "Signal and Sense: Local
and Global Order in Perceptual Maps", G.M. Edelman, W.E. Gall,
W.M. Cowan, eds., Wiley, NY, pp. 607-707
------------------------------
Subject: 68 neurosimulators
From: MURRE@rulfsw.LeidenUniv.nl
Date: Thu, 12 Mar 92 16:09:00 +0700
We have now updated and extended our table with neurosimulators to
include 68 neurosimulators. We present the table below. (Sorry, for the
many bytes taken by this format. We expect that this format is easier to
handle by everyone.)
Work on the review paper, unfortunately, has been interrupted by several
events. We plan to have something available within the next few months.
In this paper we will ponder on the possibility of deriving some
standards for a number of the 'most popular' neural networks. If we could
agree on such a set, it would be much easier to directly exchange models
and simulation scripts (at least, for this limited set of neural network
paradigms). Has anyone ever worked on this?
If anyone wants to point out errors, fill in some blanks, or prosose to
add (or remove) a system from the list, please, follow the format of the
table. Additional comments (i.e., extra references to be included in the
general review paper, background information, or reasons why a certain
entry is wrong) may then follow the changed lines.
Example:
The following line in the table ought to be changed to:
Name Manufacturer Hardware
METANET Leiden University IBM, MAC
Within 6 months from now, a MAC version will be available for this system.
Adherence to this format will make it much easier for us to deal with the
comments.
Jacob M.J. Murre Steven E. Kleyenmberg
Jacob M.J. Murre
Unit of Experimental and Theoretical Psychology
Leiden University
P.O. Box 9555
2300 RB Leiden
The Netherlands
E-mail: Murre@HLERUL55.Bitnet
tel.: 31-71-273631
fax.: 31-71-273619
N.B. At April 1 1992, I will start working at the following address:
Jacob M.J. Murre
Medical Research Council: Applied Psychology Unit
15 Chaucer Road
Cambridge CB2 2EF
England
E-mail: jaap.murre@mrc-apu.cam.ac.uk
tel.: 44-223-355294 (ext.139)
fax.: 44-223-359062
Table 1.a. Neurosimulators.
Name Manufacturer Hardware
=--------------------------------------------------------------------------
ADAPTICS Adaptic
ANNE Oregon Graduate Center Intel iPSC hypercube
ANSE TRW TWR neurocom. mark 3,4,5
ANSIM SAIC IBM
ANSKIT SAIC
ANSPEC SIAC IBM,MAC,SUN,VAX,SIGMA/DELTA
AWARENESS Neural Systems IBM
AXON HNC Inc. HNC Neurocom. ANZA,ANZA+
BOSS
BPS George Mason Univ., Fairfax IBM,VAX,SUN
BRAIN SIMULATOR Abbot,Foster & Hauserman IBM
BRAINMAKER California Scientific Software IBM
CABLE Duke University VAX
CASCOR
CASENET
COGNITRON Cognitive Software MAC,IBM
CONE IBM Palo Alto IBM
CONNECTIONS IBM
COPS Case Western Reserve Univ.
CORTEX
DESIRE/NEUNET IBM
EXPLORENET 3000 HNC Inc. IBM,VAX
GENESIS Neural Systems IBM
GENESIS/XODUS VAX,SUN
GRADSIM VAX
GRIFFIN Texas Instruments/Cambridge TI NETSIM neurocomputer
HYPERBRAIN Neurix Inc. MAC
MACBRAIN Neurix Inc. MAC
MACTIVATION University of Colorado MAC
METANET Leiden University IBM,(VAX)
MIRRORS/II University of Maryland VAX,SUN
N-NET AIWare Inc. IBM,VAX
N1000 Nestor Inc IBM,SUN
N500 Nestor Inc. IBM
NCS North Carolina State Univ. (portable)
NEMOSYS IBM RS/6000
NESTOR Nestor Inc. IBM,MAC
NET
NETSET 2 HNC Inc. IBM,SUN,VAX
NETWURKZ Dair Computer Systems IBM
NEURALSHELL Ohio State University SUN
NEURALWORKS NeuralWare Inc. IBM,MAC,SUN,NEXT,INMOS
NEURDS Digtal Equipment Corporation VAX
NEUROCLUSTERS VAX
NEURON Duke University
NEUROSHELL Ward Systems Group IBM
NEUROSOFT HNC Inc.
NEUROSYM NeuroSym Corp. IBM
NEURUN Dare research IBM
NN3/SESAME GMD, Sankt Augustin, BDR SUN
NNSIM
OPT
OWL Olmsted & Watkins IBM,MAC,SUN,VAX
P3 U.C.S.D. Symbolics
PABLO
PDP McClelland & Rumelhart IBM,MAC
PLANET University of Colorado SUN,APOLLO,ALLIANT
PLATO/ARISTOTLE NeuralTech
PLEXI Symbolics Inc/Lucid Inc Symbolics,SUN
POPLOG-NEURAL University of Sussex SUN,VAX
PREENS Nijmegen University SUN
PYGMALION Esprit SUN,VAX
RCS Rochester University SUN,MAC
SAVY TEXT RETR. SYS. Excalibur Technologies IBM,VAX
SFINX U.C.L.A.
SLONN Univ. of Southern California
SNNS Stuttgart University SUN,DEC,HP,IBM
SUNNET SUN
Table 1.b. Neurosimulators.
Name Language Models Price $
==--------------------------------------------------------------------
ADAPTICS
ANNE HLL/ILL/NDL
ANSE
ANSIM many 495
ANSKIT
ANSPEC HLL many 995
AWARENESS 275
AXON HLL 1950
BOSS
BPS C bp 100
BRAIN SIMULATOR 99
BRAINMAKER Macro bp 195
CABLE HLL
CASCOR
CASENET Prolog
COGNITRON HLL (Lisp) many 600
CONE HLL
CONNECTIONS hopf 87
COPS
CORTEX
DESIRE/NEUNET matrix
EXPLORENET 3000
GENESIS 1095
GENESIS/XODUS C
GRADSIM C
GRIFFIN
HYPERBRAIN 995
MACBRAIN many 995
MACTIVATION
METANET HLL (C) many 1000
MIRRORS/II HLL (Lisp) several
N-NET C bp 695
N1000 19000
N500
NCS HLL (C++) many
NEMOSYS
NESTOR 9950
NET
NETSET 2 many 19500
NETWURKZ 80
NEURALSHELL C many
NEURALWORKS C 1495
NEURDS C
NEUROCLUSTERS
NEURON HLL
NEUROSHELL bp 195
NEUROSOFT
NEUROSYM many 179
NEURUN bp
NN3/SESAME many
NNSIM
OPT C
OWL many 1495
P3 HLL many
PABLO
PDP several 44
PLANET HLL many
PLATO/ARISTOTLE
PLEXI Lisp,C,Pascal many
POPLOG-NEURAL HLL,POP-11 bp,cl
PREENS HLL many
PYGMALION HLL (parallel C) many
RCS C
SAVY TEXT RETR. SYS. C
SFINX HLL
SLONN
SNNS HLL many
SUNNET
Table 1.c. Neurosimulators.
Name Comments
===------------------------------------------------------------------
ADAPTICS training software for neural-networks
ANNE neural-network development environment
ANSE
ANSIM
ANSKIT development tool for large artificial neural-networks
ANSPEC
AWARENESS introductory NN program
AXON neural-network description language
BOSS
BPS
BRAIN SIMULATOR
BRAINMAKER neural-networks simulation software
CABLE
CASCOR cascade-correlation simulator
CASENET graphical case-tool for generating executable code
COGNITRON neural-network,prototyping,delivery system
CONE research environment
CONNECTIONS
COPS combinatorial optimization problems
CORTEX neural-network graphics tool
DESIRE/NEUNET interactive neural-networks experiment environment
EXPLORENET 3000 stand-alone neural-network software
GENESIS neural-network development system
GENESIS/XODUS general neural simulator, X-wnd. output, simulation utilities
GRADSIM
GRIFFIN research environment for TI NETSIM neurocomputer
HYPERBRAIN
MACBRAIN
MACTIVATION introductory neural-network simulator
METANET general neurosimulator, CAD for NN architectures
MIRRORS/II neurosimulator for parallel environments
N-NET integrated neural-network development system
N1000
N500
NCS
NEMOSYS simulation software
NESTOR
NET
NETSET 2
NETWURKZ training tool for IBM pc
NEURALSHELL
NEURALWORKS neural-networks development system
NEURDS
NEUROCLUSTERS simulation tool for biological neural networks
NEURON
NEUROSHELL
NEUROSOFT
NEUROSYM
NEURUN interactive neural-network environment
NN3/SESAME neurosimulator for modular neural networks
NNSIM mixed neural/digital image processing system
OPT all-purpose simulator
OWL
P3 early PDP development system
PABLO
PDP introductory simulator, complements 'the PDP volumes'
PLANET
PLATO/ARISTOTLE knowledge processor for expert systems
PLEXI flexible neurosimulator with graphical interaction
POPLOG-NEURAL
PREENS workbench for NN constr., visualisation,man., and simul.
PYGMALION general, parallel neurosimulator under X-Windows
RCS research environment, graphical neurosimulator
SAVY TEXT RETRIEVAL SYSTEM
SFINX research environment
SLONN
SNNS
SUNNET
Table 1.d. Neurosimulators.
Name Abbreviated reference
===------------------------------------------------------------------
ADAPTICS
ANNE
ANSE
ANSIM [Cohen, H., Neural Network Review, 3, 102-133, 1989]
ANSKIT [Barga R.S, Proc. IJCNN-90-Washington DC, 2, 94-97, 1990]
ANSPEC
AWARENESS [BYTE, 14(8), 244-245, 1989]
AXON [BYTE, 14(8), 244-245, 1989]
BOSS [Reggia J.A., Simulation, 51, 5-19, 1988]
BPS
BRAIN SIMULATOR
BRAINMAKER [BYTE, 14(8), 244-245, 1989]
CABLE [Miller J.P., Nature, 347, 783-784, 1990]
CASCOR
CASENET [Dobbins R.W, Proc. IJCNN-90-Wash. DC, 2, 122-125, 1990]
COGNITRON [BYTE, 14(8), 244-245, 1989]
CONE
CONNECTIONS [BYTE, 14(8), 244-245, 1989]
COPS [Takefuji Y., Science, 245, 1221-1223, 1990]
CORTEX [Reggia J.A., Simulation, 51, 5-19, 1988]
DESIRE/NEUNET [Korn G.A, Neural Networks, 2, 229-237, 1989]
EXPLORENET 3000 [BYTE, 14(8), 244-245, 1989]
GENESIS [Miller J.P., Nature, 347, 783-784, 1990]
GENESIS/XODUS
GRADSIM
GRIFFIN
HYPERBRAIN [BYTE, 14(8), 244-245, 1989]
MACBRAIN [BYTE, 14(8), 244-245, 1989]
MACTIVATION
METANET [Murre J.M.J., Proc. ICANN-91-FIN, 1, 545-550, 1991]
MIRRORS/II [Reggia, J.A., Simulation, 51, 5-19, 1988]
N-NET [BYTE, 14(8), 244-245, 1989]
N1000 [BYTE, 14(8), 244-245, 1989]
N500 [BYTE, 14(8), 244-245, 1989]
NCS
NEMOSYS [Miller J.P., Nature, 347, 783-784, 1990]
NESTOR
NET [Reggia J.A., Simulation, 51, 5-19, 1988]
NETSET 2
NETWURKZ [BYTE, 14(8), 244-245, 1989]
NEURALSHELL
NEURALWORKS [BYTE, 14(8), 244-245, 1989]
NEURDS
NEUROCLUSTERS
NEURON [Miller J.P., Nature, 347, 783-784, 1990]
NEUROSHELL [BYTE, 14(8), 244-245, 1989]
NEUROSOFT
NEUROSYM
NEURUN
NN3/SESAME
NNSIM [Nijhuis J.L., Microproc. & Microprogr., 27,189-94, 1989]
OPT
OWL [BYTE, 14(8), 244-245, 1989]
P3 [In: 'PDP Volume 1', MIT Press, 488-501, 1986]
PABLO
PDP [Rumelhart et al. 'Explorations in PDP', MIT Press, 1988]
PLANET
PLATO/ARISTOTLE
PLEXI
POPLOG-NEURAL
PREENS
PYGMALION
RCS
SAVY TEXT RETR. SYS. [BYTE, 14(8), 244-245, 1989]
SFINX [Mesrobian E., IEEE Int. Conf. on Man, Sys. & Cyb., 1990]
SLONN [Simulation, 55, 69-93, 1990]
SNNS
SUNNET
Explanation of abbreviations and terms:
Manufacturer: company, institute, or researchers associated with the
system
Languages: HLL = High Level Language (i.e., network definition language;
if specific programming languages are mentioned, networks
can be defined using high-level functions in these
languages)
Models: several = a fixed number of models is (and will be) supported
many = the systems can be (or will be) extended with new
models
bp = backpropagation (if specific models are mentioned,
these are the only ones supported by the system)
hopf = hopfield
cl = competitive learning
Price: indication of price range in US dollars (if no price is
this can either mean that the price is unknown to us, that the
system is not available (yet) for general distribution, or that
the system is available at a nominal charge)
Comment: attempt to indicate the primary function of the system
Reference: a single reference that contains pointers to the manufacturers,
who may be contacted for further information
(a more complete list of references, also containing review
articles, etc., will appear in a general review paper by us -
this paper is still in preparation and not yet available for
prelimary distribution [sorry])
------------------------------
End of Neuron Digest [Volume 9 Issue 15]
****************************************
