Table of Contents

• Connectivity Versus EntropyYaser S. Abu-Mostafa. 1-8 [doi]
• Stochastic Learning Networks and their Electronic ImplementationJoshua Alspector, Robert B. Allen, Victor Hu, Srinagesh Satyanarayana. 9-21 [doi]
• Learning on a General NetworkAmir F. Atiya. 22-30 [doi]
• An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme ClassificationLes E. Atlas, Toshiteru Homma, Robert J. Marks II. 31-40 [doi]
• On Properties of Networks of Neuron-Like ElementsPierre Baldi, Santosh S. Venkatesh. 41-51 [doi]
• Supervised Learning of Probability Distributions by Neural NetworksEric B. Baum, Frank Wilczek. 52-61 [doi]
• Centric Models of the Orientation Map in Primary Visual CortexWilliam Baxter, Bruce Dow. 62-71 [doi]
• Analysis and Comparison of Different Learning Algorithms for Pattern Association ProblemsJ. Bernasconi. 72-81 [doi]
• Simulations Suggest Information Processing Roles for the Diverse Currents in Hippocampal NeuronsLyle J. Borg-Graham. 82-94 [doi]
• Optimal Neural Spike ClassificationJames M. Bower, Amir F. Atiya. 95-102 [doi]
• Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real NeuronsJames M. Bower, Yiu-Fai Wong, Jashojiban Banik. 103-113 [doi]
• A Computer Simulation of Olfactory Cortex with Functional Implications for Storage and Retrieval of Olfactory InformationJames M. Bower, Matthew A. Wilson. 114-126 [doi]
• Neural Network Implementation Approaches for the Connection MachineNathan H. Brown Jr.. 127-136 [doi]
• On the Power of Neural Networks for Solving Hard ProblemsJehoshua Bruck, Joseph W. Goodman. 137-143 [doi]
• Speech Recognition Experiments with PerceptronsDavid J. Burr. 144-153 [doi]
• Presynaptic Neural Information ProcessingL. Richard Carley. 154-163 [doi]
• Mathematical Analysis of Learning Behavior of Neuronal ModelsJohn Y. Cheung, Massoud Omidvar. 164-173 [doi]
• A Neural Network Classifier Based on Coding TheoryTzi-Dar Chiueh, Rodney M. Goodman. 174-183 [doi]
• The Capacity of the Kanerva Associative Memory is ExponentialPhilip A. Chou. 184-191 [doi]
• Phase Transitions in Neural NetworksJoshua Chover. 192-200 [doi]
• New Hardware for Massive Neural NetworksDarryl D. Coon, A. G. Unil Perera. 201-210 [doi]
• High Density Associative MemoriesAmir Dembo, Ofer Zeitouni. 211-218 [doi]
• Network Generality, Training Required, and Precision RequiredJohn S. Denker, Ben S. Wittner. 219-222 [doi]
• Ensemble Boltzmann Units have Collective Computational Properties like those of Hopfield and Tank NeuronsMark Derthick, Joe Tebelskis. 223-232 [doi]
• High Order Neural Networks for Efficient Associative Memory DesignGérard Dreyfus, Isabelle Guyon, Jean-Pierre Nadal, Léon Personnaz. 233-241 [doi]
• The Sigmoid Nonlinearity in Prepyriform CortexFrank H. Eeckman. 242-248 [doi]
• Hierarchical Learning Control - An Approach with Neuron-Like Associative MemoriesE. Ersu, H. Tolle. 249-261 [doi]
• On Tropistic Processing and Its ApplicationsManuel F. Fernández. 262-269 [doi]
• Correlational Strength and Computational Algebra of Synaptic Connections Between NeuronsEberhard E. Fetz. 270-277 [doi]
• The Hopfield Model with Multi-Level NeuronsMichael Fleisher. 278-289 [doi]
• Cycles: A Simulation Tool for Studying Cyclic Neural NetworksMichael T. Gately. 290-296 [doi]
• Temporal Patterns of Activity in Neural NetworksPaolo Gaudiano. 297-300 [doi]
• Encoding Geometric Invariances in Higher-Order Neural NetworksC. Lee Giles, R. D. Griffin, T. Maxwell. 301-309 [doi]
• Probabilistic Characterization of Neural Model ComputationsRichard M. Golden. 310-316 [doi]
• Partitioning of Sensory Data by a Cortical NetworkRichard Granger, Jose A. Ambros-Ingerson, Howard Henry, Gary Lynch. 317-337 [doi]
• The Connectivity Analysis of Simple AssociationDan W. Hammerstrom. 338-347 [doi]
• Minkowski-r Back-Propagation: Learning in Connectionist Models with Non-Euclidian Error SignalsStephen Jose Hanson, David J. Burr. 348-357 [doi]
• Learning Representations by RecirculationGeoffrey E. Hinton, James L. McClelland. 358-366 [doi]
• Schema for Motor Control Utilizing a Network Model of the CerebellumJames C. Houk. 367-376 [doi]
• Experimental Demonstrations of Optical Neural ComputersKen Hsu, David Brady, Demetri Psaltis. 377-386 [doi]
• Neural Net and Traditional ClassifiersWilliam Y. Huang, Richard Lippmann. 387-396 [doi]
• An Optimization Network for Matrix InversionJu-Seog Jang, Soo-Young Lee, Sang-Yung Shin. 397-401 [doi]
• How the Catfish Tracks Its Prey: An Interactive Pipelined Processing System May Direct Foraging via Reticulospinal NeuronsJagmeet S. Kanwal. 402-411 [doi]
• Capacity for Patterns and Sequences in Kanerva s SDM as Compared to Other Associative Memory ModelsJames D. Keeler. 412-421 [doi]
• Computing Motion Using Resistive NetworksChristof Koch, Jin Luo, Carver Mead, James Hutchinson. 422-431 [doi]
• Performance Measures for Associative Memories that Learn and ForgetAnthony Kuh. 432-441 [doi]
• How Neural Nets WorkAlan S. Lapedes, Robert M. Farber. 442-456 [doi]
• Distributed Neural Information Processing in the Vestibulo-Ocular SystemClifford Lau, Vicente Honrubia. 457-466 [doi]
• Spontaneous and Information-Triggered Segments of Series of Human Brain Electric Field MapsDietrich Lehmann, D. Brandeis, A. Horst, H. Ozaki, I. Pal. 467-473 [doi]
• Optimization with Artificial Neural Network Systems: A Mapping Principle and a Comparison to Gradient Based MethodsHarrison MonFook Leong. 474-484 [doi]
• Towards an Organizing Principle for a Layered Perceptual NetworkRalph Linsker. 485-494 [doi]
• Reflexive Associative MemoriesHendricus G. Loos. 495-504 [doi]
• Connecting to the PastBruce MacDonald. 505-514 [doi]
• Microelectronic Implementations of Connectionist Neural NetworksStuart Mackie, Hans Peter Graf, Daniel B. Schwartz, John S. Denker. 515-523 [doi]
• Basins of Attraction for Electronic Neural NetworksCharles M. Marcus, R. M. Westervelt. 524-533 [doi]
• The Performance of Convex Set Projection Based Neural NetworksRobert J. Marks II, Les E. Atlas, Seho Oh, James A. Ritcey. 534-543 [doi]
• MURPHY: A Robot that Learns by DoingBartlett W. Mel. 544-553 [doi]
• Stability Results for Neural NetworksAnthony N. Michel, J. A. Farrell, Wolfgang Porod. 554-563 [doi]
• Programmable Synaptic Chip for Electronic Neural NetworksAlexander Moopenn, H. Langenbacher, A. P. Thakoor, S. K. Khanna. 564-572 [doi]
• Bit-Serial Neural NetworksAlan F. Murray, Anthony V. W. Smith, Zoe F. Butler. 573-583 [doi]
• Phasor Neural NetworksAndre J. Noest. 584-591 [doi]
• A Trellis-Structured Neural NetworkThomas Petsche, Bradley W. Dickinson. 592-601 [doi]
• Generalization of Back propagation to Recurrent and Higher Order Neural NetworksFernando J. Pineda. 602-611 [doi]
• Constrained Differential OptimizationJohn C. Platt, Alan H. Barr. 612-621 [doi]
• Learning a Color Algorithm from ExamplesTomaso Poggio, Anya C. Hurlbert. 622-631 [doi]
• Static and Dynamic Error Propagation Networks with Application to Speech CodingA. J. Robinson, F. Failside. 632-641 [doi]
• Learning by State Recurrence DetectionBruce E. Rosen, James M. Goodwin, Jacques J. Vidal. 642-651 [doi]
• Scaling Properties of Coarse-Coded Symbol MemoriesRonald Rosenfeld, David S. Touretzky. 652-661 [doi]
• An Adaptive and Heterodyne Filtering Procedure for the Imaging of Moving ObjectsF. H. Schuling, H. A. K. Mastebroek, W. H. Zaagman. 662-673 [doi]
• Pattern Class Degeneracy in an Unrestricted Storage Density MemoryChristopher L. Scofield, Douglas L. Reilly, Charles Elbaum, Leon N. Cooper. 674-682 [doi]
• A Mean Field Theory of Layer IV of Visual Cortex and Its Application to Artificial Neural NetworksChristopher L. Scofield. 683-692 [doi]
• Teaching Artificial Neural Systems to Drive: Manual Training Techniques for Autonomous SystemsJ. F. Shepanski, S. A. Macy. 693-700 [doi]
• Discovering Structure from Motion in Monkey, Man and MachineRalph M. Siegel. 701-708 [doi]
• Time-Sequential Self-Organization of Hierarchical Neural NetworksRonald H. Silverman, Andrew S. Noetzel. 709-714 [doi]
• A Computer Simulation of Cerebral Neocortex: Computational Capabilities of Nonlinear Neural NetworksAlexander Singer, John P. Donoghue. 715-729 [doi]
• Analysis of Distributed Representation of Constituent Structure in Connectionist SystemsPaul Smolensky. 730-739 [doi]
• Spatial Organization of Neural Networks: A Probabilistic Modeling ApproachAndreas Stafylopatis, Marios D. Dikaiakos, D. Kontoravdis. 740-749 [doi]
• A Dynamical Approach to Temporal Pattern ProcessingW. Scott Stornetta, Tad Hogg, Bernardo A. Huberman. 750-759 [doi]
• A Novel Net that Learns Sequential Decision ProcessGuo-Zheng Sun, Yee-Chun Lee, Hsing-Hen Chen. 760-766 [doi]
• Self-Organization of Associative Database and Its ApplicationsHisashi Suzuki, Suguru Arimoto. 767-774 [doi]
• A Neural-Network Solution to the Concentrator Assignment ProblemGene A. Tagliarini, Edward W. Page. 775-782 [doi]
• Using Neural Networks to Improve Cochlear Implant Speech PerceptionManoel Fernando Tenorio. 783-793 [doi]
• A Neural Network that Learns to Play BackgammonGerald Tesauro, Terrence J. Sejnowski. 794-803 [doi]
• Introduction to a System for Implementing Neural Net Connections on SIMD ArchitecturesSherryl Tomboulian. 804-813 [doi]
• Neuromorphic Networks Based on Sparse Optical Orthogonal CodesMario P. Vecchi, Jawad A. Salehi. 814-823 [doi]
• Synchronization in Neural NetsJacques J. Vidal, John Haggerty. 824-829 [doi]
• Invariant Object Recognition Using a Distributed Associative MemoryHarry Wechsler, George Lee Zimmerman. 830-839 [doi]
• Learning in Networks of Nondeterministic Adaptive Logic ElementsRichard C. Windecker. 840-849 [doi]
• Strategies for Teaching Layered Networks Classification TasksBen S. Wittner, John S. Denker. 850-859 [doi]
• A Method for the Design of Stable Lateral Inhibition Networks that is Robust in the Presence of Circuit ParasiticsJohn L. Wyatt Jr., D. L. Standley. 860-868 [doi]