SuperHack/SuperHack CD.bin/CODING/MISC/NUD-0943.ZIP/NUD-0943.TXT

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From: "Neuron-Digest Moderator" <[e-mail]>
To: Neuron-Distribution: ;
Subject: Neuron Digest V9 #43 (query + conference + papers)
Reply-To: "Neuron-Request" <[e-mail]>
X-Errors-To: "Neuron-Request" <[e-mail]>
Organization: University of Pennsylvania
Date: Sat, 29 Aug 92 16:44:08 -0400
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Sender: [e-mail]

Neuron Digest   Saturday, 29 Aug 1992
                Volume 9 : Issue 43

Today's Topics:
           Neural Networks for Control (specific application)
           First Swedish National Conference on Connectionism
         Preprint available: Synchronization and label-switching
                       Paper in Neuroprose Archive
            Thesis on NN simulation hardware availabe for ftp


Send submissions, questions, address maintenance, and requests for old
issues to "[e-mail]". 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: Neural Networks for Control (specific application)
From:    Duane White <[e-mail]>
Date:    Fri, 28 Aug 92 16:16:59 -0600

I need information on how to train a neural network for use with servo
motor control.

PROBLEM:

     I have a robotic arm.  The motor which controls the movement of the
arm on the Z-axis has been interfaced to a computer.  Position is read
from an encoder.  Relays are used to turn the motor on and off and to
determine the direction of the motor.  I have already developed a working
PID controller, and now would like to compare it with a neural net based
controller.  The inputs to the controller are e (position error) and e
dot (the change in error,derivative of error).
     I have already written in C++ the code for a backpropagation neural
network.  My question is "How do I go about training a neural network for
use as a CONTROLLER?"  One suggestion was to use the PID controller to
train the neural controller.  To me this is unacceptable since the neural
controller would simple be an approximation of the PID controller.  What
I would like is an idea on how to take the neural network and the arm and
perform some form of ON-LINE training.


DUANE WHITE
TEXAS A&I UNIVERSITY
DEPARTMENT OF ELECRICAL ENGINEERING, GRADUATE RESEARCH
PO BOX 2411 STA. 1
KINGSVILLE, TX 78363

[e-mail]


------------------------------

Subject: First Swedish National Conference on Connectionism
From:    Lyn Shackleton <[e-mail]>
Date:    Mon, 24 Aug 92 12:51:51 +0000



              The Connectionist Research Group
                    University of Skovde


                         The First
              Swedish National Conference on
                       Connectionism
 Wednesday 9th and Thursday 10th Sept. 1992, Skovde, Sweden
                             at
          Billingehus Hotel and Conference Centre


                        INVITED SPEAKERS

James M. Bower, California Inst. of Technology, USA
"The neuropharmacology of associative memory function: an  in
vitro,  in  vivo, and in computo study of object recognition
in olfactory cortex."

Ronald L. Chrisley, University of Sussex, UK
"Connectionist Cognitive Maps and the Development  of  Objec-
tivity."

Garrison W. Cottrell, University of California, San Diego, USA
"Dynamic Rate Adaptation."

Jerome A. Feldman, ICSI, Berkeley, USA
"Structure and Change in Connectionist Models"

Dan Hammerstrom, Adaptive Solutions, Inc., USA
"Neurocomputing Hardware: Present and Future."

James A. Hendler, University of Maryland, USA
"SCRuFFy: An applications-oriented hybrid connectionist/symbolic
shell."

Ajit Narayanan, University of Exeter, UK
"On Nativist Connectionism."

Jordan B. Pollack, Ohio State University, USA
"Explaining Cognition with Nonlinear Dynamics."

David E. Rumelhart, Stanford University, USA
"From Theory to Practice: A Case Study"

Noel E. Sharkey, University of Exeter, UK
"Semantic and Syntactic Decompositions of  Fully  Distributed
Representations"

Tim van Gelder, Indiana University, USA
"Connectionism and the Mind-Body Problem: Exposing  the  Rift
between Mind and Cognition."


                         PROGRAMME

                        Secretariat:
                          SNCC-92
                    Attn: Ulrica Carlbom
                    University of Skovde
                        P.O. Box 408
                  S-541 28 Skovde, SWEDEN
        Phone [phone], Fax [phone]
                     [e-mail]

                   Conference organisers
     Lars Niklasson (University of Skovde) [e-mail]
     Mikael Boden (University of Skovde) [e-mail]

                     Program committee
   Anders Lansner (Royal Institute of Technology, Sweden)
         Noel E. Sharkey (University of Exeter, UK)
         Ajit Narayanan (University of Exeter, UK)

                    Conference sponsors
                    University of Skovde
  The County of Skaraborg (Lansstyrelsen, Skaraborgs Lan)

                     Conference patrons
  Lars-Erik Johansson, Vice-chancellor University of Skovde
 Stig Emanuelsson, Head of Comp. Sci. Dept., Univ. of Skovde



The Swedish Neural Network Society (SNNS) will hold an offi-
cial members meeting at the conference.


                        The Sessions


                        Wednesday 9th

Session 1:      Opening / Invited Papers (Room 1)
Chair:  Lars Niklasson (SNCC-92 organiser)
08.30   Opening
09.00   Connectionism and the Mind-Body Problem:
        Exposing the Rift between Mind and Cognition
        Tim van Gelder, Indiana University, USA
09.50   Explaining Cognition with Nonlinear Dynamics
        Jordan B. Pollack, Ohio State University, USA
10.40   Coffee Break



Session 2:      Invited Paper (Room 1)
Chair:  Tim van Gelder (Indiana University, USA)
11.10 - 12.00 Semantic and Syntactic Decompositions of
        Fully Distributed Representations
        Noel E. Sharkey, University of Exeter, UK



Session 3a:     Philosophical presentations (Room 1)
Chair:  Tim van Gelder (Indiana University, USA)
12.05   Subsymbolic Connectionism: Representational Vehicles
        and Contents
        Tere Vaden, University of Tampere, Finland
12.30   First Connectionist Model of Nonmonotonic Reasoning:
        Handling Exceptions in Inheritance Hierarchies
        Mikael Boden, University of Skovde and Ajit Narayanan,
        University of Exeter, UK
12.55   Lunch Break



Session 3b:     Theoretical presentations (Room 2)
Chair:  Jordan B. Pollack (Ohio State University, USA)
12.05   Neural Networks for Unsupervised Linear
        Feature Extraction
        Reiner Lenz and Mats Osterberg, Linkoping University
12.30   Feed-forward Neural Networks in Limiting Cases of
        Infinite Nodes
        Abhay Bulsari and Henrik Saxen, Abo Akademi, Finland
12.55   Lunch Break



Session 4:      Invited Papers (Room 1)
Chair:  Jerome A. Feldman (ICSI, Berkeley, USA)
14.00   SCRuFFy: An Applications-oriented Hybrid
        Connectionist/Symbolic Shell
        James A. Hendler, University of Maryland, USA
14.50   Neurocomputing Hardware: Present and Future
        Dan Hammerstrom, Adaptive Solutions, Inc., USA
15.40   Coffee Break



Session 5a:     Philosophical presentations (Room 1)
Chair:  Noel E. Sharkey (University of Exeter, UK)
16.10   Connectionism - The Miracle Mind Model
        Lars Niklasson, University of Skovde and Noel E. Sharkey,
        University of Exeter, UK
16.35   Some Properties of Neural Representations
        Christian Balkeniun, Lund University
17.00   Behaviors, Motivations, and Perceptions In
        Artificial Creatures
        Per Hammarlund and Anders Lansner,
        Royal Institute of Technology, Stockholm
17.25   Break




Session 5b:     Hardware-oriented presentations (Room 2)
Chair:  Dan Hammerstrom (Adaptive Solutions Inc., USA)
16.10   Pulse Coded Neural Networks for Hardware
        Implementation
        Lars Asplund, Olle Gallmo, Ernst Nordstrom, and Mats Gustafsson
        Uppsala University
16.35   Towards Modular, Massively Parallel Neural Computers
        Bertil Svensson, Chalmers University of Technology, Goteborg and
        Centre for Computer Science, Halmstad University,
        Tomas Nordstrom, Lulea University of Technology,
        Kenneth Nilsson and Per-Arne Wiberg, Halmstad University
17.00   The Grid - An Experiment in Neurocomputer
        Architecture
        Olle Gallmo and Lars Asplund, Uppsala University
17.25   Break


Session 6a:     Theoretical presentations (Room 1)
Chair:  Garrison W. Cottrell (University of California, USA)
17.40   A Neural System as a Model for Image Reconstruction
        Mats Bengtsson, Swedish Defence Research
        Establishment, Linkoping
18.05   Internal Representation Models in Feedforward
        Artificial Neural Networks
        Hans G. C. Traven, Royal Institute of
        Technology, Stockholm
18.30 - 18.55   A Connectionist Model for Fuzzy Logic,
        Abhay Bulsari and Henrik Saxen, Abo Akademi, Finland



Session 6b:     Application-oriented presentations (Room 2)
Chair:  James A. Hendler (University of Maryland, USA)
17.40   A Robust Query-Reply System Based on a Bayesian
        Neural Network
        Anders Holst and Anders Lansner,
        Royal Institute of Technology, Stockholm
18.05   Neural Networks for Admission Control in an
        ATM Network
        Ernst Nordstrom, Olle Gallmo, Lars Asplund,
        Uppsala University
18.25 - 18.55   Adaptive Generalisation in Connectionist Nets
        Amanda Sharkey and Noel E Sharkey,
        University of Exeter, UK



Swedish Neural Network Society (SNNS) (Room 1)
19.00-19.45     Members meeting



                Thursday 10th

Session 7:      Invited Papers (Room 1)
Chair:  Ronald L. Chrisley (University of Sussex, UK)
09.00   Structure and Change in Connectionist Models
        Jerome A. Feldman, ICSI, Berkeley, USA
09.50   On Nativist Connectionism
        Ajit Narayanan, University of Exeter, UK
10.40   Coffee Break



Session: 8      Invited Paper (Room 1)
Chair:  Anders Lansner (Royal Institute of Technology,
Stockholm)
11.10 - 12.00   The Neuropharmacology of Associative Memory
        Function: an in Vitro, in Vivo, and in Computo
        Study of Object Recognition in Olfactory Cortex
        James M. Bower, California Institute of Technology, USA



Session 9a:     Neurobiological presentations (Room 1)
Chair:  James M. Bower (CalTech)
12.05   A Model of Cortical Associative Memory Based on
        Hebbian Cell Assemblies
        Erik Fransen, Anders Lansner and Hans Liljenstrom,
        Royal Institute of Technology, Stockholm
12.30   Cognition, Neurodynamics and Computer Models
        Hans Liljenstrom, Royal Institute of
        Technology, Stockholm
12.55   Lunch Break



Session 9b:     Application-oriented presentations (Room 2)
Chair:  David E. Rumelhart (Stanford University)
12.05   Experiments with Artificial Neural Networks for
        Phoneme and Word Recognition
        Kjell Elenius, Royal Institute of Technology, Stockholm
12.30   Recognition of Isolated Spoken Swedish Words -
        An Approach Based on a Self-organizing Feature Map
        Tomas Rahkkonen, Telia Research AB, Systems Research
        Spoken Language Processing, Haninge
12.55   Lunch Break



Session 10:     Invited Papers (Room 1)
Chair:  Ajit Narayanan (University of Exeter, UK)
14.00   Connectionist Cognitive Maps and the
        Development of Objectivity
        Ronald L. Chrisley, University of Sussex, UK
14.50   Dynamic Rate Adaption
        Garrison W. Cottrell, University of California,
        San Diego, USA
15.40   Coffee Break



Session 11:     Invited Paper (Room 1)
Chair:  Mikael Boden (SNCC-92 organiser)
16.10   From Theory to Practice: A Case Study
        David E. Rumelhart, Stanford University, USA
17.00   Closing




                     Registration form

Fees include admission to all conference sessions and a copy
of the Advance Proceedings.

Hotel reservation is made at Billingehus Hotel  and  Confer-
ence  Centre.  The  rooms  are  available from Tuesday (8th)
evening to noon Thursday (10th), for  the  two-day  alterna-
tive,  and  from  Wednesday  evening  (9th) to noon Thursday
(10th), for the one-day alternative. All activities will  be
held  at  the  conference  centre. A block of rooms has been
reserved until 10th Aug.  After this date, room reservations
will be accepted  on  a  space available basis. To register,
complete and return the form below to the secretariat.

Registration is valid  when  payment  is  received.  Payment
should  be  made  to  postal  giro  78 81 40 - 2, payable to
SNCC-92, Hogskolan i Skovde. Cancellation of hotel  reserva-
tion can be made until 15/8 (the conference fee, 600 SEK, is
not refundable).


- -------------------------- cut -----------------------------
Name: (Mr/Ms)   ____________________________________________
Company:        ____________________________________________
Address:        ____________________________________________
City/Country:   ____________________________________________
Phone:          ____________________________________________
If the double room alternative has been chosen, please give
the details for the second person.
Name: (Mr/Ms)   ____________________________________________
Company:        ____________________________________________
Country:        ____________________________________________

Alternatives                       Until 9th Aug After 9th Aug
(please circle chosen fee)

Conference fee only                1000SEK       1000SEK
(incl. coffee and lunch)

Conference fee + Full board and
single room lodging 8/9 - 10/9     2400SEK       3500SEK

Conference fee + Full board and
double room lodging 8/9 - 10/9     2 x 2000SEK   2 x 2600SEK

Conference fee + Full board and
single room lodging 9/9 - 10/9     1700SEK       2400SEK

Conference fee + Full board and
double room lodging 9/9 - 10/9     2 x 1500SEK   2 x 2000SEK


Indicate if vegetarian meals are preferred: _____ person(s)





------------------------------

Subject: Preprint available: Synchronization and label-switching
From:    Alfred_Nischwitz <[e-mail]>
Date:    Tue, 11 Aug 92 17:54:38 +0100

The following paper is submitted for publication in the proceedings of
the International Joint Conference on Artificial Neural Networks '92 in
Beijing, China:

             IMPULSE EVALUATION BY MODEL NEURONS

by  Alfred Nischwitz      Lehrstuhl fuer Nachrichtentechnik
                          Technische Universitaet Muenchen
                          Arcisstrasse 21, D-8000 Muenchen 2, Germany

ABSTRACT:

The integration of spike-input to model neurons is investigated.  The
degree of synchronization of presynaptic impulses which is necessary for
the triggering of postsynaptic action potentials is derived analytically.
It is shown that for small neural integration time constants accurate
synchronization of the incoming impulses is essential for the propagation
of the received impulses.


Hardcopies of the paper are available. Please send requests via email or
to the following address in Germany:

  Alfred Nischwitz
  Lehrstuhl fuer Nachrichtentechnik
  Technische Universitaet Muenchen
  Arcisstrasse 21, D-8000 Muenchen 2, F.R.Germany
  email: [e-mail]

Alfred Nischwitz


------------------------------

Subject: Paper in Neuroprose Archive
From:    Paolo Frasconi <[e-mail]>
Date:    Mon, 24 Aug 92 14:00:31 -0500

The following technical report has been placed in the Neuroprose
Archives at Ohio State University:

           Injecting Nondeterministic Finite State Automata
                    into Recurrent Neural Networks

            Paolo Frasconi, Marco Gori, and Giovanni Soda

              Technical Report DSI-RT15/92, August 1992
                Dipartimento di Sistemi e Informatica
                        University of Florence


Abstract:

In this paper we propose a method for injecting time-warping
nondeterministic finite state automata into recurrent neural networks.
The proposed algorithm takes as input a set of automata transition rules
and produces a recurrent architecture.  The resulting connection weights
are specified by means of linear constraints.  In this way, the network
is guaranteed to carry out the assigned automata rules, provided the
weights belong to the constrained domain and the inputs belong to an
appropriate range of values, making possible a boolean interpretation.
In a subsequent phase, the weights can be adapted in order to obtain the
desired behavior on corrupted inputs, using learning from examples.  One
of the main concerns of the proposed neural model is that it is no longer
focussed exclusively on learning, but also on the identification of
significant architectural and weight constraints derived systematically
from automata rules, representing the partial domain knowledge on a given
problem.



To obtain a copy via FTP (courtesy of Jordan Pollack):

unix% ftp archive.cis.ohio-state.edu (or 128.146.8.52)
Name: anonymous
Password: (type your E-mail address)
ftp> cd pub/neuroprose
ftp> binary
ftp> get frasconi.nfa.ps.Z
ftp> quit
unix% zcat frasconi.nfa.ps.Z | lpr
                  (or however you uncompress and print postscript)


Sorry, no hard copies available.

Paolo Frasconi
Dipartimento di Sistemi e Informatica
Via di Santa Marta, 3
50139 Firenze, Italy
[e-mail]


------------------------------

Subject: Thesis on NN simulation hardware availabe for ftp
From:    Mark James <[e-mail]>
Date:    Tue, 25 Aug 92 17:57:43 +0900

The following Master of Science thesis is available for ftp from neuroprose:


 Design of Low-cost, Real-time Simulation Systems for Large Neural Networks
 --------------------------------------------------------------------------

                             Mark James
                      The University of Sydney

                           January, 1992

                              ABSTRACT

Systems with large amounts of computing power and storage are required to
simulate very large neural networks capable of tackling complex control
problems and real-time emulation of the human sensory, language and
reasoning systems. General-purpose parallel computers do not have
communications, processor and memory architectures optimized for neural
computation and so can not perform such simulations at reasonable cost.
The thesis analyses several software and hardware strategies to make
feasible the simulation of large, brain-like neural networks in real-time
and presents a particular multicomputer design able to implement these
strategies. An important design goal is that the system must not
sacrifice computational flexibility for speed as new information about
the workings of the brain and new artificial neural network architectures
and learning algorithms are continually emerging.

The main contributions of the thesis are:

* an analysis of the important features of biological neural networks
that need to be simulated,

* a review of hardware and software approaches to neural networks, and an
evaluation of their abilities to simulate brain-like networks,

* the development of techniques for efficient simulation of brain- like
neural networks, and

* the description of a multicomputer that is able to simulate large,
brain-like neural networks in real-time and at low cost.

 ------------------------------------------
To obtain a copy via FTP
use the standard procedure:
% ftp cheops.cis.ohio-state.edu
anonymous
Password: anything
ftp> cd pub/neuroprose
ftp> binary
ftp> get james.nnsim.ps.Z
ftp> quit
% zcat james.nnsim.ps.Z | lpr



Mark James                                   |  EMAIL : [e-mail]  |
Basser Department of Computer Science, F09   |  PHONE : [phone]   |
The University of Sydney NSW 2006 AUSTRALIA  |  FAX   : [phone]   |


------------------------------

End of Neuron Digest [Volume 9 Issue 43]
****************************************