Volume 1,
Number 1,
1989
- Editorial.
1 BibTeX
- Carsten Peterson, Bo Söderberg:
A New Method for Mapping Optimization Problems Onto Neural Networks.
3-22
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- Michael G. Paulin, Mark E. Nelson, James M. Bower:
Dynamics of Compensatory Eye Movement Control: an Optimal Estimation Analysis of the Vestibulo-Ocular Reflex.
23-29
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- Pierre Peretto:
Learning Learning Sets in Neural Networks.
31-40
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- Bernardo A. Huberman:
The Collective Brain.
41-45
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- Stefano Patarnello, Paolo Carnevali:
A Neural Network Model to Simulate a Conditioning Experiment.
47-53
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- Jean-Pierre Nadal:
Study of a Growth Algorithm for a Feedforward Network.
55-59
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- Erkki Oja:
Neural Networks, Principal Components, and Subspaces.
61-68
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- Silvia Bacci, Germán Mato, Néstor Parga:
The Organization of Metastable States in A Neural Network with Hierarchichal Patterns.
69-76
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- Anders Lansner, Örjan Ekeberg:
A One-Layer Feedback Artificial Neural Network with a Bayesian Learning Rule.
77-87
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- Jens Midtgaard, Jørn Hounsgaard:
Nerve Cells as Source of Time Scale and Processing Density in Brain Function.
89-94
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- Su-shing Chen:
On Computational Vision: a Neural Processing Approach.
95-102
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Volume 1,
Number 2,
1989
- Amir F. Atiya, Pierre Baldi:
Oscillations and Synchronizations in Neural Networks: an Exploration of the Labeling Hypothesis.
103-124
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- Anthony W. Smith, David Zipser:
Learning Sequential Structure with the Real-Time Recurrent Learning Algorithm.
125-131
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- Michael R. Davenport, Geoffrey W. Hoffmann:
A Recurrent Neural Network Using Tri-State Hidden Neurons to Orthogonalize the Memory Space.
133-141
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- Harun K. M. Yusuf, Sabiha Rahman, Hasina Akhtar:
Rats Kept in Social Isolation for Twelve Months from Weaning: Performance in Maze Learning and Visual Discrimination Tests, and Brain Composition.
143-147
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- Howard C. Card, Will R. Moore:
Vlsi Devices and Circuits for Neural Networks.
149-165
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- Lars Gislén, Carsten Peterson, Bo Söderberg:
"Teachers and Classes" with Neural Networks.
167-176
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- Atilla E. Gunhan, László P. Csernai, Jørgen Randrup:
Unsupervised Competitive Learning in Neural Networks.
177-186
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- Hans-Ulrich Bauer, Theo Geisel:
Motion Detection and Direction Detection in Local Neural Nets.
187-192
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Volume 1,
Number 3,
1990
- Andreas S. Weigend, Bernardo A. Huberman, David E. Rumelhart:
Predicting the Future: a Connectionist Approach.
193-209
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- Chinchuan Chiu, Chia-Yiu Maa, Michael A. Shanblatt:
An Artificial Neural Network Algorithm for Dynamic Programming.
211-220
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- Luyuan Fang, Tao Li:
Design of Competition-Based Neural Networks for Combinatorial Optimization.
221-235
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- Edgardo A. Ferrán, Roberto P. J. Perazzo:
Dyslexic Behaviour of Feedforward Neural Networks.
237-245
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- Edoardo Milotti:
Parity and the Shapes of Neuron Transfer Functions in Feedforward Neural Networks.
247-248
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- David Horn, Marius Usher:
Excitatory-Inhibitory Networks with Dynamical Thresholds.
249-257
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- John G. Sutherland:
A Holographic Model of Memory, Learning and Expression.
259-267
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- Lei Xu:
Adding Learned Expectation Into the Learning Procedure of Self-Organizing Maps.
269-283
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- David G. Stork:
Book Review: "Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations", Patrick K. Simpson.
285-259
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Volume 1,
Number 4,
1991
Copyright © Sun May 17 00:02:46 2009
by Michael Ley (ley@uni-trier.de)