Resent: Tue, 07 Apr 92 15:29:41 -0400
Resent: ""Jaime Moraga Z" <FRANNOU%USACHVM1.bitnet@VTVM2.CC.VT.EDU> "
Resent: Tue, 07 Apr 92 15:27:29 -0400
Resent: "syc@vision.postech.ac.kr "
From: "Neuron-Digest Moderator" <neuron-request@cattell.psych.upenn.edu>
To: Neuron-Distribution: ;
Subject: Neuron Digest V9 #15 (discussion)
Reply-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu>
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Organization: University of Pennsylvania
Date: Sat, 04 Apr 92 18:17:41 EST
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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[[ Editor's Note: As long-time subscribers know, I do not publish resumes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]
****************************************
