Models Wanted: Must Fit Dimensions of Sleep and Dreaming 
J. Allan Hobson, Adam N. Mamelak, andJefj9ey P. Sutton 
 3 

Stationarity of Synaptic Coupling Strength Between Neurons with Nonstationary Discharge Properties 
Mark Sydorenko and Eric D. Young 
 11 

Perturbing Hebbian Rules 
Peter Dayan and Geoffrey Goodhill 
 19 

Statistical Reliability of a Blowfly Movement-Sensitive Neuron
Rob de Ruyter van Steveninck and William Bialek 
 27 

The Clusteron: Toward a Simple Abstraction for a Complex Neuron
Bartlett W. Mel 
 35 

Network activity determines spatio-temporal integration in single cells 
Ojvind Bernander, Christof Koch, and Rodney J. Douglas 
 43 

Nonlinear Pattern Separation in Single Hippocampal Neurons with Active Dendritic Membrane 
Anthony M, Zador, Brenda J. Claiborne, and Thomas H. Brown 
 51 

Self-organisation in real neurons: Anti-Hebb in 'Channel Space'?
Anthony J. Bell 
 59 

Single Neuron Model: Response to Weak Modulation in the Presence of Noise
A.R. Buhara, E. W. Jacobs, and E Moss 
67 

Dual Inhibitory Mechanisms for Definition of Receptive Field Characteristics in a Cat Striate Cortex 
A.B. Bonds 
 75 

A comparison between a neural netwok model for the formation of brain maps and experimental data 
K. Obermayer, K. Schulten, and G.G. Blasdel 
 83 

Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity 
Ron Keesing, David G. Stork, and Carla J. Shatz 
 91 

Locomotion in a Lower Vertebrate: Studies of the Cellular Basis of Rhythmogenesis and Oscillator Coupling 
James T. Buchanan 
 101 

Adaptive Synchronization of Neural and Physical Oscillators
Kenji Doya and Shuji Yoshizawa 
 109 

Burst Synchronization without Frequency Locking in a Completely Solvable Network Model 
Heinz Schuster and Christof Koch 
 117 

Oscillatory Model of Short Term Memory 
David Horn and Marius Usher 
 125 

Multi-State Time Delay Neural Networks for Continuous Speech Recognition
Patrick Haffner and Alex Waibel
 135 

Modeling Applications with the Focused Gamma Net 
Jose C. Principe, Bert de l&ies, Jyh Ming Kuo, Pedro Guedes de Oliveira 
 143 

Time-Warping Network: A Hybrid Framework for Speech Recognition 
Esther Levin, Roberto Pieraccini, and Enrico Bocchieri 
 151 

Improved Hidden Markov Model Speech Recognition Using Radial Basis Function Networks 
Elliot Singer and Richard P. Lippmann 
 159 

Connectionist Optimisation of Tied Mixture Hidden Markov Models 
Steve Renals, Nelson Morgan, Hervd Bourlard, Horacio Franco, and Michael Cohen 
 167 

Neural Network Gaussian Mixture Hybrid for Speech Recognition or Density Estimation 
Yoshua Bengio, Renato De Mori, Giovanni Flammia, Ralf Kompe 
 175 

JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques 
Alex Waibel, Ajay N. Jain, Arthru McNair, Joe Tebelskis, Louise Osterhohz, Hiroaki Saito, Otto Schmidbauer, Tilo Sloboda, and Monika Woszczyna 
 183 

Forward Dynamics Modeling of Speech Motor Control Using Physiological Data 
Makoto Hirayama, Eric l&tikiotis-Bateson, Mitsuo Kawato, and Michael I. Jordan 
 191 

English Alphabet Recognition with Telephone Speech 
Mark Fancy, Ronald A. Cole, and Krist Roginski 
 199 

Generalization Performance in PARSEC--A Structured Connectionist Parsing Architecture 
Ajay N. Jain 
 209 

Constructing Proofs in Symmetric Networks 
Gadi Pinkas 
 217 

A Connectionist Learning Approach to Analyzing Linguistic Stress 
Prahlad Gupta and David S. lburetzky 
 225 

Propagation Filters in PDS Networks for Sequencing and Ambiguity Resolution 
Ronald A. Sumida and Michael G. Dyer 
 233 

A Segment-based Automatic Language Identification System 
Yeshwant K. Muthusamy and Ronald A. Cole 
 241 

The Efficient Learning of Multiple Task Sequences 
Satinder P. Singh 
 251 

Practical Issues in Temporal Difference Learning 
Gerald Tesauro 
 259 

HARMONET: A Neural Net for Harmonizing Chorales in the Style of J.S. Bach 
Hermann Hild, Johannes Feulner, and Wolfram Menzel 
 267 

Induction of Multiscale Temporal Structure 
Michael C. Mozer 
 275 

Network Model of State-Dependent Sequencing 
Jeffrey P. Sutton, Adam N. Mamelak, and jr. Allan Hobson 
 283 

Learning Unambiguous Reduced Sequence Descriptions 
Jurgen Schmidhuber 
 291 

Recurrent Networks and NARMA Modeling 
Jerome Connor, Les E. Atlas, and Douglas R. Martin 
 301 

Induction of Finite-State Automata Using Second-Order Recurrent Networks 
Raymond L. Watrous, and Gary M. Kuhn 
309 

Extracting and Learning an Unknown Grammar with Recurrent Neural Networks 
C.L. Giles, C.B. Miller, D. Chen, G.Z. Sun, H.H. Chen, and Y.C. Lee 
 317 

Operators and curried functions: Training and analysis of simple recurrent networks 
Janet Wiles and Anthony Bloesch 
 325 

Green's Function Method for Fast On-line Learning Algorithm of Recurrent Neural Networks 
Guo-Zheng Sun, Hsing-Hen Chen, and Yee-Chun Lee 
 333 

Dynamically-Adaptive Winner-Take-All Networks 
Bent E. Lange 
 341 

Information Processing to Create Eye Movements 
David A. Robinson 
 351 

Decoding of Neuronal Signals in Visual Pattern Recognition 
Emad N. Eskandar, Barry J. Richmond, John A. Hertz, 
 356 

Lance M. Optican, and 3oels Kjter Learning How to Teach or Selecting Minimal Surface Data 
Davi Geiger and Ricardo A. Marques Pereira 
 364 

Learning to Make Coherent Predictions in Domains with Discontinuities 
Suzanna Becker and GeofJ3ey E. Hinton 
 372 

Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion 
PA. V7ola, S.G. Lisberger, and T.J. Sejnowski 
 380 

Against Edges: Function Approximation with Multiple Support Maps 
Trevor Darrell and Alex Pentland 
 388 

Markov Random Fields Can Bridge Levels of Abstraction 
Paul R. Cooper and Peter N. Prokopowicz 
 396 

Illumination and View Position in 3D Visual Recognition 
Amnon Shashua 
 404 

Hierarchical Transformation of Space in the Visual System 
Alexandre Pouget, Stephen A. Fisher, and Terrence J. Sejnowski 
 412 

VISI15 A Neural Model of Covert Visual Attention 
Subutai Ahmad 
 420 

Visual Grammars and their Neural Nets 
Eric Mjohness 
 428 

Learning to Segment Images Using Dynamic Feature Binding 
Michael C. Mozer, Richard S. Zemel, and Marlene Behrmann 
 436 

Combined Neural Network and Rule-Based Framework for Probabilistic Pattern Recognition and Discovery 
Hayit K. Greenspan, Rodney Goodman, and Rama Chellappa 
 444 

Linear Operator for Object Recognition 
Ronen Basri and Shimon Ullman 
 452 

3D Object Recognition Using Unsupervised Feature Extraction 
Nathan Intrator, Josh L Gold, Heinrich H. Biihhoff, and Shimon Edelman 
 460 

Structural Risk Minimization for Character Recognition 
I. Guyon, V. Vapnik, B. Boser, L. Bottou, and S.A. Solla 
 471 

Image Segmentation with Networks of Variable Scales 
Hans P. Graf, Craig R. Nohl, and Jan Ben 
 480 

Multi-Digit Recognition Using a Space Displacement Neural Network 
Ofer Matan, ChristopherJ. C. Burges, Yann Le Cun, and John S. Denker 
 488 

A Self-Organizing Integrated Segmentation and Recognition Neural Net 
Jim Keeler and David E. Rumelhart 
 496 

Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition 
Gale L. Martin and Mosfeq Rashid 
 504 

Adaptive Elastic Models for Hand-Printed Character Recognition 
Geoffrey E. Hinton, Christophe K.I. Williams, and Michael D. Revow 
 512 

Obstacle Avoidance through Reinforcement Learning 
73nyJ. Prescott and John E. W. Mayhew 
 523 

Active Exploration in Dynamic Environments 
Sebastian B. Thrun and Knut Mgller 
 531 

Oscillatory Neural Fields for Globally Optimal Path Planning 
Michael Lemmon 
 539 

Recognition of Manipulated Objects by Motor Learning 
Hiroaki Gomi and Mitsuo Kawato 
 547 

Refining PID Controllers using Neural Networks 
Gary M. Scott, Jude W. Shavlik, and W. Harmon Ray 
 555 

Fast Learning with Predictive Forward Models 
Carlos Brody 
 563 

Fast, Robust Adaptive Control by Learning only Forward Models 
Andrew W. Moore 
 571 

Reverse TDNN: An Architecture for Trajectory Generation 
Patrice Simard and Yann Le Cun 
 579 

Learning Global Direct Inverse Kinematics 
David DeMers and Kenneth Kreutz-Delgado 
 589 

A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem 
Paul Dean, John E. W. Mayhew, and Pat Langdon 
 595 

Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation 
Thomas J. Anastasio 
 603 

A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm 
N.E. Berthier, S.P. Singh, A.G. Barto, andJ. C. Houk 
 611 

A Computational Mechanism to Account for Averaged Modified Hand Trajectories 
Ealan A. Henis and Tamar Flash 
 619 

Simulation of Optimal Movements Using the Minimum-Muscle-Tension-Change Model 
Menashe Dornay, Yoji Uno, Mitsuo Kawato, and Ryoji Suzuki 
 627 

ANN Based Classification for Heart Defibrillators 
M. Jabri, S. Pickard, P. Leong, Z. Chi, B. Flower, and Y. Xie 
 637 

Neural Network Diagnosis of Avascular Necrosis from Magnetic Resonance Images 
Armando Manduca, Paul Christy, and Richard Ehman 
 645 

Neural Network Analysis of Event Related Potentials and Electroencephalogram Predicts Vigilance 
Rita lOnturini, William W. Lytton, and Terrence J. Sejnowski 
 651 

Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency 
Martin Rgscheisen, Reimar Holmann, and Volker Tresp 
 659 

Fault Diagnosis of Antenna Pointing Systems Using Hybrid Neural Network and Signal Processing Models 
Padhraic Smyth and Jeff Mellstrom 
 667 

Multimodular Architecture for Remote Sensing Options 
Sylvie Thiria, Carlos Mejia, Fouad Badran, Michel Crgpon 
 675 

Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction 
John Moody and Joachim Utans 
 683 

Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes 
Sheri L. Gish and Mario Blaum 
 691 

Application of Neural Network Methodology to the Modelling of the Yield Strength in a Steel Rolling Plate Mill 
Ah Chung 73oi 
 698 

Computer Recognition of Wave Location in Graphical Data by a Neural Network 
Donald T. Freeman 
 706 

A Neural Network for Motion Detection of Drift-Balanced Stimuli 
Hilary Tunley 
 714 

Neural Network Routing for Random Multistage Interconnection Networks
Mark W. Goudreau and C. Lee Giles 
722 

Networks for the Separation of Sources that are Superimposed and Delayed . . 
John C. Platt and Federico Faggin 
730 

CCD Neural Network Processors for Pattern Recognition 
Alice M. Chiang, Michad L. Chuang, and JerSey R. LaFranchise 
 741 

A Parallel Analog CCD/CMOS Signal Processor 
Charles E Neugebauer andAmnon Yariv 
 748 

Direction Selective Silicon Retina that uses Null Inhibition 
Ronald G. Benson and labi Delbriick 
 756 

A Contrast Sensitive Silicon Retina with Reciprocal Synapses 
Kwabena A. Boahen and Andreas G. Andreou 
 764 

A Neurocomputer Board Based on the ANNA Neural Network Chip 
Eduard Sa'ckinger, Bernhard E. Boser, and Lawrence D. Jackal 
 773 

Software for ANN training on a Ring Array Processor 
Phil Kohn, Jeff Bilmes, Nelson Morgan, and James Beck 
 781 

Constrained Optimization Applied to the Parameter Setting Problem  for Analog Circuits 
David IOrk, Kurt Fleischer, Lloyd Watts, and Alan Barr 
 789 

Segmentation Circuits Using Constrained Optimization 
John G. Harris 
 797 

Analog LSI Implementation of an Auto-Adaptive Network for Real-Time Separation of Independent Signals 
Marc H. Cohen, Phillipe O. Pouliquen, and Andreas G. Andreou 
 805 

Temporal Adaptation in a Silicon Auditory Nerve 
John Lazzaro 
 813 

Optical Implementation of a Self-Organizing Feature Extractor 
Dana Z. Anderson, Claus Benkert, Verena Hebler, Ju-SeogJang, 
 821 

Don Montgomery, and Mark Saffman Principles of Risk Minimization for Learning Theory 
V. Papnik 
 831 

Bayesian Model Comparison and Backprop Nets 
DavidJ. C. MacKay 
 839 

The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems 
John E. Moody 
 847 

Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods 
David Haussler, Michad Kearns, Manned Opper, and Robert Schapire 
 855 

Constant-Time Loading of Shallow 1-Dimensional Networks 
Stephen Judd 
 863 

Experimental Evaluation of Learning in a Neural Microsystem 
Joshua Alspector, Anthony Jayakumar, and Stephan Luna 
 871 

Threshold Network Learning in the Presence of Equivalences 
John Shawe-Taylor 
 879 

Gradient Descent: Second Order Momentum and Saturating Error 
Barak Pearlmutter 
 887 

Tangent Prop--A formalism for specifying selected invariances in an adaptive network 
Patrice Simard, Bernard Victorri, Yann Le Cun, and John Denker 
 895 

Polynomial Uniform Convergence of Relative Frequencies to Probabilities 
Alberto Bertoni, Paola Campadelli, Anna Morpurgo, and Sandra Panizza 
 904 

Unsupervised learning of distributions on binary vectors using 2- layer networks 
Yoav Freund and David Haussler 
 912 

Incrementally Learning Time-varying Half-planes 
Anthony Kuh, Thomas Petsche, and Ron L. Rivest 
 920 

The VC-Dimension versus the Statistical Capacity of Multilayer Networks 
Chuanyi Ji and Demetri Psahis 
 928 

Some Approximation Properties of Projection Pursuit Learning Networks 
lS'ng Zhao and Christopher G. Atkeson 
 936 

Neural Computing with Small Weights 
Kai-Yeung Siu and Jehoshua Bruck 
 944 

A Simple Weight Decay Can Improve Generalization 
Anders Krogh and John A. Hertz 
 950 

Best-First Model Merging for Dynamic Learning and Recognition 
Stephen M. Omohundro 
 958 

Rule Induction through Integrated Symbolic and Subsymbolic Processing 
Clayton McMillan, Michad C. Mozer, and Paul Smolensky 
 969 

Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules 
Geoffrey lawell and Jude W. Shavlik 
 977 

Hierarchies of adaptive experts 
Michad I. Jordan and Robert A. Jacobs 
 985 

Adaptive Soft Weight Tying using Gaussian Mixtures 
Steven J. Nowlan and Geoffrey E. Hinton 
 993 

Repeat Until Bored: A Pattern Selection Strategy 
Paul W. Munro 
 1001 

Towards Faster Stochastic Gradient Search 
Christian Darken and John Moody 
 1009 

Competitive Anti-Hebbian Learning of Invariants 
Nicol N. Schraudolph and 7brrence J. Sejnowski 
 1017 

Merging Constrained Optimisation with Deterministic Annealing to "Solve" Combinatorially Hard Problems 
Paul Stolorz 
 1025 

Kernel Regression and Backpropagation Training with Noise 
Patri Koistinen and Lasse Holmstrom 
 1033 

Splines, Rational Functions and Neural Networks 
Robert C. lgSlliamson and Peter L. Bartlett 
 1040 

Networks with Learned Unit Response Functions 
John Moody and Norman Yarvin 
 1048 

Learning in Feedforward Networks with Nonsmooth Functions 
Nicholas J. Redding and T. Downs 
 1056 

Iterative Construction of Sparse Polynomial Approximations 
Terence D. Sanger, Richard S. Sutton, and Christopher J. Matheus 
 1064 

Node Splitting: A Contructive Algorithm for Feed-Forward Neural Networks 
Mike Wynne-Jones 
1072 

Information Measure Based Skeletonisation 
Sowmya Ramachandran and Lorien Y. Pratt 
 1080 

Data Analysis Using G/Splines 
David Rogers 
 1088 

Unsupervised Classifiers, Mutual Information and 'Phantom Targets' . 
John S. Bridle, Anthony J. R. Heading, and DavidJ. C. MacKay 
 1096 

A Network of Localized Linear Discriminants 
Martin S. Glassman 
 1102 

A Weighted Probabilistic Neural Network 
David Montana 
 1110 

Network generalization for production: Learning and producing styled letterforms 
Igor Grebert, David G. Stork, Ron Keesing, and Steve Mims 
 1118 

Shooting Craps in Search of an Optimal Strategy for Training Connectionist Pattern Classifiers 
J.B. Hampshire H and B. V.K. 55jaya Kumar 
 1125 

Improving the Performance of Radial Basis Function Networks by Learning Center Locations 
Dietrich lY&ttschereck and Thomas Dietterich 
 1133 

A Topograhic Product for the Optimization of Self-Organizing Feature Maps . . 
Ham-Ulrich Bauer, Klaus Pawelzik, and Theo Geisd 
1141 

Human and Machine 'Quick Modeling' . 
Jakob Bernasconi and Karl Gustaj5on 
 1151 

A Comparison of Projection Pursuit and Neural Network Regression Modeling 
Jenq-Neng Hwang, Hang Li, Martin Maechler, R. Douglas Martin, and Jim Schimert 
 1159 

Benchmarking Feed-Forward Neural Networks: Models and Measures 
Leonard G.C. Hamey 
 1167 

