Neural Computation, Volume 5

Volume 5, Number 1, January 1993

• M. Griniasty, M. V. Tsodyks, Daniel J. Amit:
  Conversion of Temporal Correlations Between Stimuli to Spatial Correlations Between Attractors. 1-17
  

• Ji-Nan Lin, Rolf Unbehauen:
  On the Realization of a Kolmogorov Network. 18-20
  

• Leonid Kruglyak, William Bialek:
  Statistical Mechanics for a Network of Spiking Neurons. 21-31
  
• Michael E. Hasselmo:
  Acetylcholine and Learning in a Cortical Associative Memory. 32-44
  
• Joseph J. Atick, A. Norman Redlich:
  Convergent Algorithm for Sensory Receptive Field Development. 45-60
  
• Nathan Intrator, Joshua I. Gold:
  Three-Dimensional Object Recognition Using an Unsupervised BCM Network: The Usefulness of Distinguishing Features. 61-74
  
• Joachim M. Buhmann, Hans Kühnel:
  Complexity Optimized Data Clustering by Competitive Neural Networks. 75-88
  
• Yiu-fai Wong:
  Clustering Data by Melting. 89-104
  
• Gustavo Deco, Jürgen Ebmeyer:
  Coarse Coding Resource-Allocating Network. 105-114
  
• James A. Kottas:
  Training Periodic Sequences Using Fourier Series Error Criterion. 115-131
  
• Yoshikane Takahashi:
  Generalization and Approximation Capabilities of Multilayer Networks. 132-139
  
• Shun-ichi Amari, Noboru Murata:
  Statistical Theory of Learning Curves under Entropic Loss Criterion. 140-153
  
• Erol Gelenbe:
  Learning in the Recurrent Random Neural Network. 154-164
  

Volume 5, Number 2, March 1993

• O. Nerrand, Pierre Roussel-Ragot, Léon Personnaz, Gérard Dreyfus, S. Marcos:
  Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms. 165-199
  

• Rajagopal Srinivasan, Hillel J. Chiel:
  Fast Calculation of Synaptic Conductances. 200-204
  
• Peter Dayan, Terrence J. Sejnowski:
  The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning. 205-209
  
• Gary D. Kendall, Trevor J. Hall:
  Optimal Network Construction by Minimum Description Length. 210-212
  

• Diana E. J. Blazis, Thomas M. Fischer, Thomas J. Carew:
  A Neural Network Model of Inhibitory Information Processing in Aplysia. 213-227
  
• Christiane Linster, Claudine Masson, Michel Kerszberg, Léon Personnaz, Gérard Dreyfus:
  Computational Diversity in a Formal Model of the Insect Olfactory Macroglomerulus. 228-241
  
• Sungzoon Cho, James A. Reggia:
  Learning Competition and Cooperation. 242-259
  
• David E. Cairns, Roland J. Baddeley, Leslie S. Smith:
  Constraints on Synchronizing Oscillator Networks. 260-266
  
• Suzanna Becker, Geoffrey E. Hinton:
  Learning Mixture Models of Spatial Coherence. 267-277
  
• Yaser S. Abu-Mostafa:
  Hints and the VC Dimension. 278-288
  
• A. Norman Redlich:
  Redundancy Reduction as a Strategy for Unsupervised Learning. 289-304
  
• Jooyoung Park, Irwin W. Sandberg:
  Approximation and Radial-Basis-Function Networks. 305-316
  
• Somnath Mukhopadhyay, Asim Roy, Lark Sang Kim, Sandeep Govil:
  A Polynomial Time Algorithm for Generating Neural Networks for Pattern Classification: Its Stability Properties and Some Test Results. 317-330
  
• Mattias Ohlsson, Carsten Peterson, Bo Söderberg:
  Neural Networks for Optimization Problems with Inequality Constraints: The Knapsack Problem. 331-339
  

Volume 5, Number 3, May 1993

• Michel Kerszberg, Jean-Pierre Changeux:
  A Model for Motor Endplate Morphogenesis: Diffusible Morphogens, Transmembrane Signaling, and Compartmentalized Gene Expression. 341-358
  

• Neil E. Cotter, Peter R. Conwell:
  Universal Approximation by Phase Series and Fixed-Weight Networks. 359-362
  
• Liping Yang, Wanzhen Yu:
  Backpropagation with Homotopy. 363-366
  
• Jane Bromley, John S. Denker:
  Improving Rejection Performance on Handwritten Digits by Training with "Rubbish". 367-370
  
• Peter L. Bartlett:
  Vapnik-Chervonenkis Dimension Bounds for Two- and Three-Layer Networks. 371-373
  

• Markus Lappe, Josef P. Rauschecker:
  A Neural Network for the Processing of Optic Flow from Ego-Motion in Man and Higher Mammals. 374-391
  
• Peter Dayan:
  Arbitrary Elastic Topologies and Ocular Dominance. 392-401
  
• Pierre Baldi, Yves Chauvin:
  Neural Networks for Fingerprint Recognition. 402-418
  
• Gale L. Martin:
  Centered-Object Integrated Segmentation and Recognition of Overlapping Handprinted Characters. 419-429
  
• Alex Pentland:
  Surface Interpolation Networks. 430-442
  
• Nathan Intrator:
  Combining Exploratory Projection Pursuit and Projection Pursuit Regression with Application to Neural Networks. 443-455
  
• Andrew D. Back, Ah Chung Tsoi:
  A Simplified Gradient Algorithm for IIR Synapse Multilayer Perceptrons. 456-462
  
• Toshiaki Tanaka, Miki Yamada:
  The Characteristics of the Convergence Time of Associative Neural Networks. 463-472
  
• P. Kerlirzin, F. Vallet:
  Robustness in Multilayer Perceptrons. 473-482
  
• Thorsteinn Rögnvaldsson:
  Pattern Discrimination Using Feedforward Networks: A Benchmark Study of Scaling Behavior. 483-491
  
• Charles R. Rosenberg, Jacob Erel, Henri Atlan:
  A Neural Network That Learns to Interpret Myocardial Planar Thallium Scintigrams. 492-502
  

Volume 5, Number 4, July 1993

• Bruce Denby:
  The Use of Neural Networks in High-Energy Physics. 505-549
  

• E. R. Grannan, D. Kleinfeld, Haim Sompolinsky:
  Stimulus-Dependent Synchronization of Neuronal Assemblies. 550-569
  

• Marius Usher, Heinz G. Schuster, Ernst Niebur:
  Dynamics of Populations of Integrate-and-Fire Neurons, Partial Synchronization and Memory. 570-586
  
• Catherine H. Ferrar, Thelma L. Williams, Graham Bowtell:
  The Effects of Cell Duplication and Noise in a Pattern Generating Network. 587-596
  
• Kechen Zhang, Martin I. Sereno, Margaret E. Sereno:
  Emergence of Position-Independent Detectors of Sense of Rotation and Dilation with Hebbian Learning: An Analysis. 597-612
  
• Peter Dayan:
  Improving Generalization for Temporal Difference Learning: The Successor Representation. 613-624
  
• Jürgen Schmidhuber, Daniel Prelinger:
  Discovering Predictable Classifications. 625-635
  
• M. Migliore, G. F. Ayala:
  A Kinetic Model of Short- and Long-Term Potentiation. 636-647
  
• John G. Elias:
  Artificial Dendritic Trees. 648-664
  

Volume 5, Number 5, September 1993

• Andrew Nicoll, Colin Blakemore:
  Patterns of Local Connectivity in the Neocortex. 665-680
  
• Erik De Schutter, James M. Bower:
  Sensitivity of Synaptic Plasticity to the Ca²⁺ Permeability of NMDA Channels: A Model of Long-Term Potentiation in Hippocampal Neurons. 681-694
  
• Yair Weiss, Shimon Edelman, Manfred Fahle:
  Models of Perceptual Learning in Vernier Hyperacuity. 695-718
  
• Wolfgang Konen, Christoph von der Malsburg:
  Learning to Generalize from Single Examples in the Dynamic Link Architecture. 719-735
  
• David Horn, Eytan Ruppin, Marius Usher, M. Herrmann:
  Neural Network Modeling of Memory Deterioration in Alzheimer's Disease. 736-749
  
• A. Norman Redlich:
  Supervised Factorial Learning. 750-766
  
• Mostefa Golea, Mario Marchand:
  On Learning Perceptrons with Binary Weights. 767-782
  
• Dhananjay S. Phatak, Hoon Choi, Israel Koren:
  Construction of Minimal n-2-n Encoders for Any n. 783-794
  
• Vicente López, Ramón Huerta, José R. Dorronsoro:
  Recurrent and Feedforward Polynomial Modeling of Coupled Time Series. 795-811
  
• Patrik Floréen, Pekka Orponen:
  Attraction Radii in Binary Hopfield Nets are Hard to Compute. 812-821
  

Volume 5, Number 6, November 1993

• L. F. Abbott, Gwendal Le Masson:
  Analysis of Neuron Models with Dynamically Regulated Conductances. 823-842
  

• Adam F. Strassberg, Louis J. DeFelice:
  Limitations of the Hodgkin-Huxley Formalism: Effects of Single Channel Kinetics on Transmembrane Voltage Dynamics. 843-855
  
• Alexander Borst, Martin Egelhaaf, H. S. Seung:
  Two-Dimensional Motion Perception in Flies. 856-868
  
• David S. Touretzky, A. David Redish, Hank S. Wan:
  Neural Representation of Space Using Sinusoidal Arrays. 869-884
  
• Jeffrey N. Kidder, Daniel Seligson:
  Fast Recognition of Noisy Digits. 885-892
  
• Vladimir Vapnik, Léon Bottou:
  Local Algorithms for Pattern Recognition and Dependencies Estimation. 893-909
  
• An Mei Chen, Haw-minn Lu, Robert Hecht-Nielsen:
  On the Geometry of Feedforward Neural Network Error Surfaces. 910-927
  
• Henry Leung, Simon Haykin:
  Rational Function Neural Network. 928-938
  
• Marc M. Van Hulle, Dominique Martinez:
  On an Unsupervised Learning Rule for Scalar Quantization following the Maximum Entropy Principle. 939-953
  
• Visakan Kadirkamanathan, Mahesan Niranjan:
  A Function Estimation Approach to Sequential Learning with Neural Networks. 954-975
  
• Zheng Zeng, Rodney M. Goodman, Padhraic Smyth:
  Learning Finite State Machines With Self-Clustering Recurrent Networks. 976-990