Neural Networks: Artificial Intelligence and Industrial Applications: Proceedings of the Third Annual SNN Symposium on Neural Networks, Nijmegen, The Netherlands, 14–15 September 1995

397 Pages·1995·12.188 MB·English

by  Reinhard Eckhorn (auth.), Bert Kappen, Stan Gielen (eds.)

Neural Networks:
Artificial Intelligence and Industrial Applications
Springer
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Bert Kappen and Stan Gielen (Eds)
Neural Networks:
Artificial Intelligence and
Industrial Applications
Proceedings of the Third Annual SNN Symposium
on Neural Networks, Nijmegen, The Netherlands,
14-15 September 1995
, Springer
Bert Kappen and Stan Gielen
Dutch Foundation for Neural Networks (SNN)
Geert Grooteplein Noord 21
6525 EZ Nijmegen
The Netherlands
ISBN-13:978-3-540-19992-2 e-ISBN-13:978-1-4471-3087-1
DOl: 10.10071978-1-4471-3087-1
British Library Cataloguing in Publication Data
Neural Networks: Artificial Intelligence
and Industrial Applications -Proceedings
of the Third Annual SNN Symposium on
Neural Networks. Nijmegen. The
Netherlands. 14-15 September 1995
l. Kappen. Bert II. GieIen. Stan
006.3
ISBN-13: 978-3-540-19992-2
Library of Congress Cataloging-in-Publication Data
A catalog record for this book is available from the Library of Congress
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Preface
This volume contains a collection of papers that were presented during the
Third Annual Symposium on Neural Networks in Nijmegen, The Netherlands.
The symposium was held on September 14 and 15 1995 and was organised by the
Dutch Foundation for Neural Networks (SNN). The symposium consisted of two
parallel tracks.
The scientific track is entitled Neural Networks and Artificial Intelligence. The
term "Artificial Intelligence" is often associated with "traditional AI"
methodology. Here it is used in its literal sense, indicating the problem to create
intelligence by artificial means.
When considering the possibility of artificial intelligence, it is important to
realise that we would never consider such a thing without the example of natural
intelligence. Therefore, design of artificial intelligence should take advantage of
the biological solutions. This is the research field called neural networks.
The aim of the scientific track is two-fold: to give an overview of new
developments in neuro-biology and the cognitive sciences. These insights may
lead to novel computational paradigms for artificial intelligence. Secondly, to give
an overview of recent technical and theoretical achievements in robotics, vision
and data modeling.
Until recently the use of neural networks has been restricted to the academic
world. However, over the last few years industries and businesses have started to
become aware of the benefits of neural networks for commercial use. Their ability
to learn by examples, to deal with noisy data and with nonlinear structures makes
neural networks suitable to deal with problems where conventional computing
fails. These abilities of neural networks result in various commercial advantages:
such as for instance improved accuracy and system performance, the ability to
automate previously manual processes, and reduced development effort. The
ultimate proof of the commercial benefits of neural computing is given by the
rapidly increasing number of applications.
The industrial track is entitled Neural Networks in Practice. As is emphasised
by this title, the industrial track presents working neural network solutions to real
industrial problems. The aim of the track is to convince industry and business that
neural networks provide solutions where other methods fail. To illustrate that
neural computation is not restricted to any specific industrial area, the
presentations have been selected from a broad range of application areas, varying
from industrial process control to marketing and finance. Finally we would like to
stress that most presentations concern applications which are at this moment in
commercial use.
This industrial track is one of the activities of the Stimulation Initiative for
European Neural Applications (SIENA). SIENA is an Esprit project (EP 9811)
whose objective is to accelerate the take-up of Neural Network technology in
Europe through a program of activities with a specifically industrial orientation.
vi
SNN is a partner in SIENA for the Benelux, in a multinational consortium with
other partners in the United Kingdom, Spain, France and Germany.
We would like to thank the industrial program committee and our colleagues
in the SIENA project for their invaluable assistance in the design of the industrial
program. We would like to thank the scientific program committee for their help
in the review of the scientific program. Finally, we would like to thank Elma Burg
for her great help in the preparation of these proceedings.
Bert Kappen
Stan Gielen
Organisation
Scientific Program Committee:
A. Aertsen (Jerusalem), S.I. Amari (Tokyo), J. Buhmann (Bonn), B. van Dijk
(Amsterdam), R. Eckhorn (Marburg), S. Gielen (Nijmegen), T. Heskes
(Nijmegen), A. Herz (Oxford), B. Kappen (Nijmegen), B. Krose (Amsterdam), V.
Lopez (Madrid), D. Mackay (Cambridge), T. Martinetz (MUnchen), J. Taylor
(London), W. von Seelen (Bochum).
Industrial Program Committee:
E. Auee (Arnhem), S. Hafner (Stuttgart), T. Harris (Egham, Surrey), B. Kappen
(Nijmegen), W. Wiegerinck (Nijmegen), T. Willems (Oisterwijk).
This symposium is organised by the Foundation for Neural Networks (SNN).
InnovatieCentrum Midden-en Zuid-Gelderland (IC) and Vereniging Artificiele
Neurale Netwerken (V ANN) collaborated in the organisation of the industrial
track.
The Foundation for Neural Networks (SNN) is a university-based non-profit
making organisation that stimulates fundamental and applied research on neural
networks in the Netherlands. The research program investigates neural
information processing strategies for artificial behaviour, vision, pattern
recognition and cognitive systems and various application areas. SNN collaborates
with industry on neural solutions for their specific industrial applications.
Currently, several groups from the universities of Nijmegen, Utrecht, Amsterdam,
Delft and Groningen are participating. (Contact address: Geert Grooteplein 21,6525
EZ Nijmegen, The Netherlands, tel [phone], fax [phone], e-mail
[email protected]. After 10 October 1995: tel + 31 243614245, fax [phone].)
InnovatieCentrum Midden-en Zuid-Gelderland (IC) is an initiative of the Dutch
Ministry of Economic Affairs to make knowledge accessible and applicable for
small and medium-sized enterprises. IC operates on the basis of independent and
individual advice. Also in the field of neural networks IC helps entrepreneurs of
SMEs to investigate whether this technology can be useful in their specific
situation. (Contact address: E. Auee, Bergstraat 35-4, 6811 LC Arnhem, The
Netherlands, tel [phone], fax [phone], e-mail Ed_Auee.ICNN.ICNN
[email protected]. After 10 October 1995: tel [phone], fax
[phone].)
De Vereniging Artificiele Neurale Netwerken (V ANN) is an independent
association. It offers its members (academics and industrials) an informal forum
to discuss neural networks and their applications. The VA NN is the Dutch Special
viii
Interest Group of the International Neural Network Society and yearly organises 5
mini-symposia on practical applications of neural networks. To keep its members
and others interested a year-book is published. (Contact address: D.J.N. Egberts,
Julianalaan 35, 6721 ED Bennekom, The Netherlands, e-mail [email protected]).
Contents
NEURAL NETWORKS AND ARTIFICIAL INTELLIGENCE
Neurobiology -Orals
Segmentation Coding by the Visual System -Neural Signals that
Possibly Support Scene Segmentation
R. Eckhorn ................................................................................................................. 5
Synchrony and Fast Plasticity in the Visual Cortex
B. W. van Dijk ............................................................................................................ 13
Rapid Neural Synchronization: From Spiking Cells to Synfire Webs
A. V.M. Herz............................................................................................................... 21
Dynamic Representations Provide the Gradual Specification of
Movement Parameters
K. Kopecz. W. Erlhagen and G. Schoner ................................................................. 29
Recording from Foveal Striate Cortex While the Monkey is Looking at
the Stimulus
J. Kruger.!. Bondar and H. Haan............................................................................ 33
Propagation of Synfire Activity in Cortical Networks -A Statistical
Approach
M.-O. Gewaltig, M. Diesmann and A. Aertsen....................................................... 37
Propagation of Synfire Activity in Cortical Networks -A Dynamical
Systems Approach
M. Arndt. W. Erlhagen and A. Aertsen................................................................... 41
Neurobiology -Posters
Aspects of Spatiotemporal Learning in Artificial Neural Networks:
Modelling Synaptic Membrane Currents Using SPICE Simulations
J. Hoekstra and P. Mantel........................................................................................ 47
Possible Functional Roles of the Bipartite Dendrites of Pyramidal Cells
R. Moller and H.-M. Grop........................................................................................ 51
The Role of Cerebellum in Motor Control
F. Mechsner ............................................................................................................... 55
x
A Point Process Approach to Cortical Networks
s.
Rotter and A. Aertsen........................................................................................... 59
Stochastic Resonance and Multi-Modal Firing Patterns in Single
Neuron Models
D. Linders and B. Kappen ........................................................................................ 63
Cognitive Modelling and Rule Extraction -Orals
The BB Neural Network Rule Extraction Method
F.R. Wiersma, M. Poel and A.M. Oudshoff............................................................. 69
Implications of Hadley's Definition of Systematicity
N. Bakker ................................................................................................................... 73
The Binding Problem in Distributed Systems
P.H. de Vries and G.]. Dalenoort............................................................................. 77
Integrating Symbolic and Sub symbolic Architectures for Parsing
Arithmetic Expressions and Natural Language Sentences
].A. Tepper, H. Powell and D. Palmer-Brown......................................................... 81
Bayesian Strategies for Machine Learning: Rule Extraction and Concept
Detection
L. Martignon and K.B. Laskey................................................................................. 85
Cognitive Modelling and Rule Extraction -Posters
Learning at Subsymbolic and Symbolic Levels
A. Grurnbach ............................................................................................................. 91
The Construction of Evaluative Maps: Affective Computations in the
Amygdala
E.P. Fulcher ............................................................................................................... 95
Computation, Cognition and Neural Networks
F. van der Velde........................................................................................................ 99
Automatic Speech Recognition Systems and Models of Human Word
Recognition: A Comparative Analysis
P. Wittenburg, D. van Kuijk and K. Behnke........................................................... 103
Language Acquisition and the Necessity of a New Neural Network
Approach
K. Behnke and P. Wittenburg .................................................................................. 107
A Neural Model of Visual Attention
P. van de Laar, T. Heskes and S. Gielen.................................................................. 111