0003	Models Wanted: Must Fit Dimensions of Sleep and Dreaming J. Allan Hobson, Adam N. Mamelak, and Jeffrey P. Sutton
0011	Stationarity of Synaptic Coupling Strength Between Neurons with Nonstationary Discharge Properties Mark Sydorenko and Eric D. Young
0019	Perturbing Hebbian Rules Peter Dayan and Geoffrey Goodhill
0027	Statistical Reliability of a Blowfly Movement-Sensitive Neuron Rob de Ruyter van Steveninck and William Bialek
0035	The Clusteron: Toward a Simple Abstraction for a Complex Neuron Bartlett W. Mel
0043	Network activity determines spatio-temporal integration in single cells Ojvind Bernander, Christof Koch, and Rodneyl Douglas
0051	Nonlinear Pattern Separation in Single Hippocampal Neurons with Active Dendritic Membrane Anthony M. Zador, Brendaf Clai borne, and Thomas H. Brown
0059	Self-organisation in real neurons: Anti-Hebb in 'Channel Space'? Anthony J. Bell
0067	Single Neuron Model: Response to Weak Modulation in the Presence of Noise A.R. Bulsara, E.W. Jacobs, and F. Moss
0075	Dual Inhibitory Mechanisms for Definition of Receptive Field Characteristics in a Cat Striate Cortex A.B. Bonds
0083	A comparison between a neural netwok model for the formation of brain maps and experimental data K. Obermszyer, K. Schulten, and G. G. Blasdel

Part II NEURO-DYNAMICS

0091	Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity Ron Keesing, David G. Stork, and Carla J. Shatz
0101	Locomotion in a Lower Vertebrate: Studies of the Cellular Basis of Rhythmogenesis and Oscillator Coupling James T. Buchanan
0109	Adaptive Synchronization of Neural and Physical Oscillators Kenji Doya and Shuji Yoshizawa
0117	Burst Synchronization without Frequency Locking in a Completely Solvable Network Model Heinz Schuster and Christof Koch

Part III SPEECH

0125	Oscillatory Model of Short Term Memory David Horn and Marius Usher
0135	Multi-State Time Delay Neural Networks for Continuous Speech Recognition Patrick Haffner andAlex Waibel
0143	Modeling Applications with the Focused Gamma Net Jose C. Principe, Bert de Vries, Jyh Ming Kuo, Pedro Guedes de Oliveira
0151	Time-Warping Network: A Hybrid Framework for Speech Recognition Esther Levin, Roberto Pieraccini, and Enrico Bocchieri
0159	Improved Hidden Markov Model Speech Recognition Using Radial Basis Function Networks Elliot Singer and Richard P. Lippmann
0167	Connectionist Optimisation of Tied Mixture Hidden Markov Models Steve Renals, Nelson Morgan, Herve Bourlard, Horacio Franco, and Michael Cohen
0175	Neural Network--Gaussian Mixture Hybrid for Speech Recognition or Density Estimation Yoshua Bengio, Renato De Mori, Giovanni Flammia, Ralf Kompe
0183	JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques Alex Waibel, Ajay N. fain, Arthru McNair, Joe Tebelskis, Louise Osterholtz, Hiroaki Saito, Otto Schmidbauer, Tilo Sloboda, and Monika Woszczyna
0191	Forward Dynamics Modeling of Speech Motor Control Using Physiological Data Makoto Hirayama, Eric Vatikiotis-Bateson, Mitsuo Kawato, and Michael I. Jordan

Part IV LANGUAGE

0199	English Alphabet Recognition with Telephone Speech Mark Fanty, Ronald A. Cole, and Krist Roginski
0209	Generalization Performance in PARSEC-A Structured Connectionist Parsing Architecture Ajay N. fain
0217	Constructing Proofs in Symmetric Networks Gadi Pinkas
0225	A Connectionist Learning Approach to Analyzing Linguistic Stress Prahlad Gupta and David S. Thuretzky
0233	Propagation Filters in PDS Networks for Sequencing and Ambiguity Resolution Ronald A. Sumida and Michael G. Dyer

Part V TEMPORAL SEQUENCES

0241	A Segment-based Automatic Language Identification System Yeshwant K. Muthusamy and Ronald A. Cole
0251	The Efficient Learning of Multiple Task Sequences Satinder P. Singh
0259	Practical Issues in Temporal Difference Learning Gerald Tesauro
0267	HARMONET: A Neural Net for Harmonizing Chorales in the Style of J.S. Bach Hermann Hild, Johannes Feulner, and Wolfram Menzel
0275	Induction of Multiscale Temporal Structure Michael C. Mozer
0283	Network Model of State-Dependent Sequencing Jeffley P. Sutton, Adam N. Mamelak, and J. Allan Hobson

Part VI RECURRENT NETWORKS

0291	Learning Unambiguous Reduced Sequence Descriptions Jurgen Schmidhuber
0301	Recurrent Networks and NARMA Modeling Jerome Connor, Les E. Atlas, and Douglas R. Martin
0309	Induction of Finite-State Automata Using Second-Order Recurrent Networks Raymond L. Watrous, and Gary M. Kuhn
0317	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
0325	Operators and curried functions: Training and analysis of simple recurrent networks Janet Wiles and Anthony Bloesch
0333	Green's Function Method for Fast On-line Learning Algorithm of Recurrent Neural Networks Guo-Zheng Sun, Hsing-Hen Chen, and Yee-Chun Lee

PartVII VISION

0341	Dynamically-Adaptive Winner-Take-All Networks Trent E. Lange
0351	Information Processing to Create Eye Movements David A. Robinson
0356	Decoding of Neuronal Signals in Visual Pattern Recognition Emad N. Eskandar, Barryf. Richmond, John A. Hertz, Lance M. Optican, and Troels Kjer
0364	Learning How to Teach or Selecting Minimal Surface Data Davi Geiger and Ricardo A. Marques Pereira
0372	Learning to Make Coherent Predictions in Domains with Discontinuities Suzanna Becker and Geoffley E. Hinton
0380	Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion P.A. Viola, S. G. Lisberger, and T.J. Sejnowski
0388	Against Edges: Function Approximation with Multiple Support Maps Trevor Darrell and Alex Pentland
0396	Markov Random Fields Can Bridge Levels of Abstraction Paul R. Cooper and Peter N. Prokopowicz
0404	Illumination and View Position in 3D Visual Recognition Amnon Shashua
0412	Hierarchical Transformation of Space in the Visual System Alexandre Pouget, Stephen A. Fisher, and Terrence J. Sejnowski
0420	VISIT: A Neural Model of Covert Visual Attention Subutai Ahmad
0428	Visual Grammars and their Neural Nets Eric Mjolsness
0436	Learning to Segment Images Using Dynamic Feature Binding Michael C. Mozer, Richard S. Zemel, and Marlene Behrmann
0444	Combined Neural Network and Rule-Based Framework for Probabilistic Pattern Recognition and Discovery Hayit K. Greenspan, Rodney Goodman, and Rama Chellappa
0452	Linear Operator for Object Recognition Ronen Basri and Shimon Ullman

Part VIII OPTICAL CHARACTER RECOGNITION

0460	3D Object Recognition Using Unsupervised Feature Extraction Nathan Intrator, Josh I. Gold, Heinrich H. Bulthoffi and Shimon Edelman
0471	Structural Risk Minimization for Character Recognition I. Guyon, V. Vapnik, B. Boser, L. Bottou, and S.A. Solla
0480	Image Segmentation with Networks of Variable Scales Hans P. Graf, Craig R. Nohl, and Jan Ben
0488	Multi-Digit Recognition Using a Space Displacement Neural Network Ofer Matan, Christopher J. C. Burges, Yann Le Cun, and John S. Denker
0496	A Self-Organizing Integrated Segmentation and Recognition Neural Net Jim Keeler and David E. Rumelhart
0504	Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition Gale L. Martin and Mosfeq Rashid

Part IX CONTROL AND PLANNING

0512	Adaptive Elastic Models for Hand-Printed Character Recognition Geoffrey E. Hinton, Christophe K.I. Williams, and Michael D. Revow
0523	Obstacle Avoidance through Reinforcement Learning Tony J. Prescott and John E. W. Mayhew
0531	Active Exploration in Dynamic Environments Sebastian B. Thrun and Knut Moller
0539	Oscillatory Neural Fields for Globally Optimal Path Planning Michael Lemmon
0547	Recognition of Manipulated Objects by Motor Learning Hiroaki Gomi and Mitsuo Kawato
0555	Refining PID Controllers using Neural Networks Gary M. Scott, Jude W. Shavlik, and W. Harmon Ray
0563	Fast Learning with Predictive Forward Models Carlos Brody
0571	Fast, Robust Adaptive Control by Learning only Forward Models Andrew W. Moore
0579	Reverse TDNN: An Architecture for Trajectory Generation Patrice Simard and Yann Le Cun
0589	Learning Global Direct Inverse Kinematics David DeMers and Kenneth Kreutz-Delgado
0595	A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem Paul Dean, John E. W. Mayhew, and Pat Langdon
0603	Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation Thomas J. Anastasio
0611	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, and J.C. Houk
0619	A Computational Mechanism to Account for Averaged Modified Hand Trajectories Ealan A. Henis and Tamar Flash

Part X APPLICATIONS

0627	Simulation of Optimal Movements Using the Minimum-Muscle-Tension-Change Model Menashe Dornay, Yoji Uno, Mitsuo Kawato, and Ryoji Suzuki
0637	ANN Based Classification for Heart Defibrillators M. Jabri, S. Pickard, P. Leong, Z. Chi, B. Flower, and Y. Xie
0645	Neural Network Diagnosis of Avascular Necrosis from Magnetic Resonance Images Armando Manduca, Paul Christy, and Richard Ehman
0651	Neural Network Analysis of Event Related Potentials and Electroencephalogram Predicts Vigilance Rita Venturini, William W. Lytton, and Terrence J. Sejnowski
0659	Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency Martin Roscheisen, Reimar Hofmann, and Volker Tresp
0667	Fault Diagnosis of Antenna Pointing Systems Using Hybrid Neural Network and Signal Processing Models Padhraic Smyth and Jeff Mellstrom
0675	Multimodular Architecture for Remote Sensing Options Sylvie Thiria, Carlos Mejia, Fouad Badran, Michel Crepon
0683	Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction John Moody and Joachim Utans
0691	Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes Sheri L. Gish and Mario Blaum
0698	Application of Neural Network Methodology to the Modelling of the Yield Strength in a Steel Rolling Plate Mill Ah Chung Tsoi
0706	Computer Recognition of Wave Location in Graphical Data by a Neural Network Donald T. Freeman
0714	A Neural Network for Motion Detection of Drift-Balanced Stimuli Hilary Tunley
0722	Neural Network Routing for Random Multistage Interconnection Networks Mark W. Goudreau and C. Lee Giles

Part XI IMPLEMENTATION

0730	Networks for the Separation of Sources that are Superimposed and Delayed John C. Platt and Federico Faggin
0741	CCD Neural Network Processors for Pattern Recognition Alice M. Chiang, Michael L. Chuang, and Jeffrey R. LaFranchise
0748	A Parallel Analog CCD/CMOS Signal Processor Charles F. Neugebauer and Amnon Yariv
0756	Direction Selective Silicon Retina that uses Null Inhibition Ronald G. Benson and Tobi Delbruck
0764	A Contrast Sensitive Silicon Retina with Reciprocal Synapses Kwabena A. Boahen and Andreas G. Andreou
0773	A Neurocomputer Board Based on the ANNA Neural Network Chip Eduard Sackinger, Bernhard E. Boser, and Lawrence D. Jackel
0781	Software for ANN training on a Ring Array Processor Phil Kohn, Jeff Bilmes, Nelson Morgan, and James Beck
0789	Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits David Kirk, Kurt Fleischer, Lloyd Watts, and Alan Barr
0797	Segmentation Circuits Using Constrained Optimization John G. Harris
0805	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
0813	Temporal Adaptation in a Silicon Auditory Nerve John Lazzaro

Part XII LEARNING AND GENERALIZATION

0821	Optical Implementation of a Self-Organizing Feature Extractor Dana Z. Anderson, Claus Benkert, Verena Hebler, Ju-Seog Jang, Don Montgomery, and Mark Saffman
0831	Principles of Risk Minimization for Learning Theory V. Vapnik
0839	Bayesian Model Comparison and Backprop Nets David J. C. MacKay
0847	The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems John E. Moody
0855	Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods David Haussler, Michael Kearns, Manfred Opper, and Robert Schapire
0863	Constant-Time Loading of Shallow 1-Dimensional Networks Stephen Judd
0871	Experimental Evaluation of Learning in a Neural Microsystem Joshua Alspector, Anthony Jayakumar, and Stephan Luna
0879	Threshold Network Learning in the Presence of Equivalences John Shawe-Taylor
0887	Gradient Descent: Second Order Momentum and Saturating Error Barak Pearlmutter
0895	Tangent Prop--A formalism for specifying selected invariances in an adaptive network Patrice Simard, Bernard Victorri, Yann Le Cun, and John Denker
0904	Polynomial Uniform Convergence of Relative Frequencies to Probabilities Alberto Bertoni, Paola Campadelli, Anna Morpurgo, and Sandra Panizza
0912	Unsupervised learning of distributions on binary vectors using 2-layer networks Yoav Freund and David Haussler
0920	Incrementally Learning Time-varying Half-planes Anthony Kuh, Thomas Petsche, and Ron L. Rivest
0928	The VC-Dimension versus the Statistical Capacity of Multilayer Networks Chuanyi Ji and Demetri Psaltis
0936	Some Approximation Properties of Projection Pursuit Learning Networks Ying Zhao and Christopher G. Atkeson
0944	Neural Computing with Small Weights Kai-Yeung Siu and Jehoshua Bruck
0950	A Simple Weight Decay Can Improve Generalization Anders Krogh and John A. Hertz

Part XIII ARCHITECTURES AND ALGORITHMS

0958	Best-First Model Merging for Dynamic Learning and Recognition Stephen M. Omohundro
0969	Rule Induction through Integrated Symbolic and Subsymbolic Processing Clayton McMillan, Michael C. Mozer, and Paul Smolensky
0977	Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules Geoffiry Towell and Jude W. Shavlik
0985	Hierarchies of adaptive experts Michael I. Jordan and Robert A. Jacobs
0993	Adaptive Soft Weight Tying using Gaussian Mixtures Steven J. Nowlan and Geoffrey E. Hinton
1001	Repeat Until Bored: A Pattern Selection Strategy Paul W. Munro
1009	Towards Faster Stochastic Gradient Search Christian Darken and John Moody
1017	Competitive Anti-Hebbian Learning of Invariants Nicol N. Schraudolph and Terrence J. Sejnowski
1025	Merging Constrained Optimisation with Deterministic Annealing to "Solve" Combinatorially Hard Problems Paul Stolorz
1033	Kernel Regression and Backpropagation Training with Noise Patti Koistinen and Lasse Holmstrom
1040	Splines, Rational Functions and Neural Networks Robert C. Williamson and Peter L. Bartlett
1048	Networks with Learned Unit Response Functions John Moody and Norman Yarvin
1056	Learning in Feedforward Networks with Nonsmooth Functions Nicholas J. Redding and T. Downs
1064	Iterative Construction of Sparse Polynomial Approximations Terence D. Sanger, Richard S. Sutton, and Christopher J. Matheus
1072	Node Splitting: A Contructive Algorithm for Feed-Forward Neural Networks Mike Wynne-Jones
1080	Information Measure Based Skeletonisation Sowmya Ramachandran and Lorien Y. Pratt
1088	Data Analysis Using G/Splines David Rogers
1096	Unsupervised Classifiers, Mutual Information and 'Phantom Targets' John S. Bridle, Anthony J.R. Heading, and David J. C. MacKay
1102	A Network of Localized Linear Discriminants Martin S. Glassman
1110	A Weighted Probabilistic Neural Network David Montana
1118	Network generalization for production: Learning and producing styled letterforms Igor Grebert, David G. Stork, Ron Keesing, and Steve Mims
1125	Shooting Craps in Search of an Optimal Strategy for Training Connectionist Pattern Classifiers J.B. Hampshire II and B.V.K. VijayaKumar
1133	Improving the Performance of Radial Basis Function Networks by Learning Center Locations Dietrich Wettschereck and Thomas Dietterich

Part XIV PERFORMANCE COMPARISONS

1141	A Topograhic Product for the Optimization of Self-Organizing Feature Maps Hans-Ulrich Bauer, Klaus Pawelzik, and Theo Geisel
1151	Human and Machine 'Quick Modeling' Jakob Bernasconi and Karl Gustafson
1159	A Comparison of Projection Pursuit and Neural Network Regression Modeling Jenq-Neng Hwang, Hang Li, Martin Maechler, R. Douglas Martin, and Jim Schimert
1167	Benchmarking Feed-Forward Neural Networks: Models and Measures Leonard G.C. Hamey
1175	Keyword Index
1184	Author Index