Part 1: Coding and Learning in Biology

• 
  Wolfram Schultz: Reward Responses of Dopamine Neurons: A Biological Reinforcement Signal. 3-12
• 
  Henry Markram, Misha Tsodyks: The Information Content of Action Potential Trains - A Synaptic Basis. 13-23
• 
  Robert Miller: Cortical Cell Assemblies, Laminar Interaction, and Thalamocortical Interplay. 25-30
• 
  Nicolas Brunel: Cross-Correlations in Sparsely Connected Recurrent Networks of Spiking Neurons. 31-36
• 
  Igor V. Tetko, Alessandro E. P. Villa: A Comparative Study of Pattern Detection Algorithm and Dynamical System Approach Using Simulated Spike Trains. 37-42
• 
  Jean Rouat: Spatio-Temporal Pattern Recognition with Neural Networks: Application to Speech. 43-48
• 
  Petr Lánský, Vera Lánská: Noise in Integrate-and-Fire Models of Neuronal Dynamics. 49-54
• 
  Christian W. Eurich, Hubert R. Dinse, Ulrike Dicke, Ben Godde, Helmut Schwegler: Coarse Coding Accouts for Improvement of Spatial Discrimination after Plastic Reorganization in Rats and Humans. 55-60
• 
  Simon R. Schultz, Stefano Panzeri, Alessandro Treves, Edmund T. Rolls: Analogue Resolution in a Model of the Schaffer Collaterals. 61-66
• 
  Maurizio Mattia, Stefano Fusi: Modeling Networks with Linear (VLSI) Integrate-and-Fire Neurons. 67-72
• 
  Gustavo Deco, Bernd Schürmann: An Information-Theoretic Analysis of Temporal Coding Strategies by Spiking Central Neurons. 73-78
• 
  Raphael Ritz, Terrence J. Sejnowski: Correlation Coding in Stochastic Neural Networks. 79-84
• 
  Akira Hirose: Two-Dimensional Hodgkin-Huxley Equations for Investigating a Basis of Pulse-Processing Neural Networks. 85-90
• 
  Edgar Körner, Ursula Körner: Concurrent Parallel-Sequential Processing in Gamma Controlled Cortical-Type Networks of Spiking Neurones. 91-96
• 
  Leslie S. Smith: A Noise-Robust Auditory Modelin Front End for Voiced Speech. 97-102
• 
  Tuong Vinh Ho, Jean Rouat: A Novelty Detector Using a Network of Integrate and Fire Neurons. 103-108
• 
  Julian Eggert, J. Leo van Hemmen: Derivation of Pool Dynamics from Microscopic Neuronal Models. 109-114
• 
  Volker Steuber, David J. Willshaw: How a Single Purkinje Cell Could Learn the Adaptive Timing of the Classically Conditioned Eye-Blink Response. 115-120
• 
  Walter Senn, Misha Tsodyks, Henry Markram: An Algorithm for Synaptic Modification Based on Exact Timing of Pre- and Post-Synaptic Action Potentials. 121-126
• 
  Lubica Benusková: Modeling Plasticity in Rat Barrel Cortex Induced by One Spared Whisker. 127-132
• 
  Raymond Kohli, Peter G. H. Clarke: Mathematical Analysis of Competition Between Sensory Ganglion Cells for Nerve Growth Factor in the Skin. 133-138
• 
  Arjen van Ooyen, David J. Willshaw: Competition Amongst Neurons for Neurotrophins. 139-144
• 
  Manuel Samuelides, Simon J. Thorpe, Emmanuel Veneau: Implementing Hebbian Learning in a Rank-Based Neural Network. 145-150
• 
  Bruce Graham, David J. Willshaw: A Model of Clipped Hebbian Learning in a Neocortical Pyramidal Cell. 151-156
• 
  Christian W. Eurich, Jack D. Cowan, John G. Milton: Hebbian Delay Adaptation in a Network of Integrate-and-Fire Neurons. 157-162
• 
  András Lörincz: Hippocampal Formation Trains Independent Components via Forcing Input Reconstruction. 163-168

Part 2: Cortical Maps and Receptive Fields

• 
  Siegrid Löwel, Kerstin E. Schmidt, Wolf Singer: Nature vs. Nurture in the Development of Tangential Connections and Functional Maps in the Visual Cortex. 171-176
• 
  Mark Hübener, Doron Shoham, S. Schulze, G. Brändle, Amiram Grinvald, Tobias Bonhoeffer: Geometric Relationships Between Feature Maps in Cat Visual Cortex. 177-182
• 
  Stefan Wimbauer, Oliver G. Wenisch, J. Leo van Hemmen: A Linear Hebbian Model for the Development of Spatiotemporal Receptive Fields of Simple Cells. 183-188
• 
  Martin Stetter, Elmar Wolfgang Lang, Klaus Obermayer: Synapse Clustering Can Drive Simultaneous ON-OFF and Ocular-Dominance Segregation in a Model of Area 17. 189-194
• 
  Fred Wolf, Theo Geisel: Must Pinwheels Move During Visual Development? 195-200
• 
  Francesco Frisone, Luca Perico, Pietro Morasso: Extending the TRN Model in a Biologically Plausible Way. 201-206
• 
  Dirk Brockmann, Hans-Ulrich Bauer, Maximilian Riesenhuber, Theo Geisel: SOM-Model for the Development of Oriented Receptive Fields and Orientation Maps from Non-oriented ON-center OFF-center Inputs. 207-212
• 
  Ute Bauer, Péter Adorján, Michael Scholz, Jonathan B. Levitt, Jennifer S. Lund, Klaus Obermayer: On the Anatomical Basis of Field Size, Contrast Sensitivity, and Orientation Selectivity in Macaque Striate Cortex: A Model Study. 213-218
• 
  Christian Ziegaus, Elmar Wolfgang Lang: Statistics of Natural and Urban Images. 219-224
• 
  Thomas Burger, Elmar Wolfgang Lang: A CBL Network Model with Intracortical Plasticity and Natural Image Stimuli. 225-230
• 
  Udo Ernst, Klaus Pawelzik, Fred Wolf, Theo Geisel: Geometry of Orientation Preference Map Determines Nonclassical Receptive Field Properties. 231-236
• 
  Hauke Bartsch, Martin Stetter, Klaus Obermayer: A Model for Orientation Tuning and Contextual Effects of Orientation Selective Receptive Fields. 237-242
• 
  Laurenz Wiskott, Terrence J. Sejnowski: Objective Functions for Neural Map Formation. 243-248
• 
  Klaus Kopecz, Karim Mohraz: Relative Time Scales in the Self-Organization of Pattern Classification: From One-Shot to Statistical Learning. 249-254
• 
  Jinhui Chao, Yasuhiko Miyata, Shinichi Yoshida: Realization of Geometric Illusions and Geometry of Visual Space with Neural Networks. 255-260

Part 3: Learning: Theory and Algorithms

• 
  Vladimir Vapnik: The Support Vector Method. 263-271
• 
  Richard S. Sutton: On the Significance of Markov Decision Processes. 273-282
• 
  Nathalie Chatenet, Hugues Bersini: Economical Reinforcement Learning for Non Stationary Problems. 283-288
• 
  Thomas Czernichow: A Double Gradient Algorithm to Optimize Regularization. 289-294
• 
  N. P. Bradshaw, Antoine Duchâteau, Hugues Bersini: Global Least-Squares vs. EM Training for the Gaussian Mixture of Experts. 295-300
• 
  Hilbert J. Kappen, Francisco de Borja Rodríguez Ortiz: Accelerated Learning in Boltzmann Machines Using Mean Field Theory. 301-306
• 
  Siegfried Bös: Adaptive Online Learning for Nonstationary Problems. 307-312
• 
  Maissa Aboukassem, Steffen Schwember, Steffen Noehte, Reinhard Männer: Weight Discretization due to Optical Constraints and Its Influence on the Generalization Abilities of a Simple Perceptron. 313-318
• 
  Skander Soltani, Stéphane Canu, Daniel Boichu, Yves Grandvalet: Wavelet Frames Based Estimator. 319-324
• 
  Nasser Mozayyani, Gilles Vaucher: A Spatio-temporal Perceptron for On-Line Handwritten Character Recognition. 325-330
• 
  Martin Georg Weiß: Learning Oscillations Using Adaptive Control. 331-336
• 
  Peter Eggenberger: Creation of Neural Networks Based on Developmental and Evolutionary Principles. 337-342
• 
  Alberto Bertoni, Paola Campadelli, M. Parodi: A Boosting Algorithm for Regression. 343-348
• 
  Michiaki Taniguchi, Volker Tresp: Combining Regularized Neural Networks. 349-354
• 
  Stefan M. Rüger: Making Stochastic Networks Deterministic. 355-360
• 
  Berthold Ruf, Michael Schmitt: Unsupervised Learning in Networks of Spiking Neurons Using Temporal Coding. 361-366
• 
  Arto Selonen, Jouko Lampinen: Experiments on Regularizing MLP Models with Background Knowledge. 367-372
• 
  Steffen Gutjahr, Joachim Feist: Elliptical Basis Function Networks for Classification Tasks. 373-378
• 
  Ingo Galleske, Juan Castellanos: Probabilistic Neural Networks with Rotated Kernel Functions. 379-384
• 
  Norbert Jankowski, Visakan Kadirkamanathan: Statistical Control of RBF-like Networks for Classification. 385-390
• 
  Matthias Scherf, Wilfried Brauer: Improving RBF Networks by the Feature Selection Approach EUBAFES. 391-396
• 
  Ingo Graf, Ulrich Kressel, Jürgen Franke: Polynominal Classifiers and Support Vector Machines. 397-402
• 
  Masahiro Kimura, Ryohei Nakano: Unique Representations of Dynamical Systems Produced by Recurrent Neural Networks. 403-408
• 
  Barbara Hammer: Generalization of Elman Networks. 409-414
• 
  Masumi Ishikawa, Kazuhiko Nishino: Designing Neural Networks by a Combination of Structural Learning and Genetic Algorithms. 415-420
• 
  Markus Varsta, José del R. Millán, Jukka Heikkonen: A Recurrent Self-Organizing Map for Temporal Sequence Processing. 421-426
• 
  Peter Stagge, Bernhard Sendhoff: An Extended Elman Net for Modeling Time Series. 427-432
• 
  Margarita Kuzmina, Eduard A. Manykin, Irina Surina: Recurrent Associative Memory Network of Nonlinear Coupled Oscillators. 433-438
• 
  Heiko Wersing, Jochen J. Steil, Helge Ritter: A Layered Recurrent Neural Network for Feature Grouping. 439-444
• 
  Kürt Meert, Jacques Ludik: A Multilayer Real-Time Recurrent Learning Algorithm for Improved Convergence. 445-450
• 
  Amos J. Storkey: Increasing the Capacity of a Hopfield Network without Sacrificing Functionality. 451-456
• 
  Hui Wang, David A. Bell: A Novel Associative Network Accomodating Pattern Deformation. 457-462
• 
  Yves Grandvalet, Stéphane Canu: Adaptive Noise Injection for Input Variables Relevance Determination. 463-468
• 
  Piërre van de Laar, Stan C. A. M. Gielen, Tom Heskes: Input Selection with Partial Retraining. 469-474
• 
  Eddy Mayoraz: On the Complexity of Recognizing Iterated Differences of Polyhedra. 475-480
• 
  Yann Guermeur, Florence d'Alché-Buc, Patrick Gallinari: Optimal Linear Regression on Classifier Outputs. 481-486
• 
  Régis Quélavoine, Pascal Nocera: Learning Verification in Multilayer Neural Networks. 487-492
• 
  Oh Jun Kwon, Sung Yang Bang: Design of a Fault Tolerant Multilayer Perceptron with a Desired Level of Robustness. 493-498
• 
  Perry Moerland: Mixtures of Experts Estimate A Posteriori Probabilities. 499-504
• 
  Axel Doering, Miroslaw Galicki, Herbert Witte: Admissibility and Optimality of the Cascade-Correlation Algorithm. 505-510
• 
  N. P. Bradshaw: The Effective VC Dimension of the n-tuple Classifier. 511-516

Part 4: Signal Processing: Blind Source Separation, Vector Quantization, and Self-Organization

• 
  Erkki Oja, Juha Karhunen, Aapo Hyvärinen: From Neural Principal Components to Neural Independent Components. 519-528
• 
  Anisse Taleb, Christian Jutten: Entropy Optimization - Application to Blind Source Separation. 529-534
• 
  Bert-Uwe Koehler, Te-Won Lee, Reinhold Orglmeister: Improving the Performance of Infomax Using Statistical Signal Processing Techniques. 535-540
• 
  Petteri Pajunen, Juha Karhunen: A Maximum Likelihood Approach to Nonlinear Blind Source Separation. 541-546
• 
  Marco Mattavelli, Edoardo Amaldi, Jean-Marc Vesin: A Perceptron-Based Approach to Piecewise Linear Modeling with an Application to Time Series. 547-552
• 
  Erkki Oja, Kimmo Valkealahti: Local Independent Component Analysis by the Self-Organizing Map. 553-558
• 
  Georges Linares, Pascal Nocera, Henri Meloni: Model Breaking Detection Using Independent Component Classifier. 559-564
• 
  Anisoara Paraschiv-Ionescu, Christian Jutten, Gérard Bouvier: Neural Network Based Processing for Smart Sensors Arrays. 565-570
• 
  Simone Fiori, Aurelio Uncini, Francesco Piazza: Application of the MEC Network to Principal Component Analysis and Source Separation. 571-576
• 
  Jyrki Joutsensalo: Semi-Blind Source Parameter Separation. 577-582
• 
  Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Kernel Principal Component Analysis. 583-588
• 
  Thiagarajan Balachander, Ravi Kothari, Hernani Cualing: An Empirical Comparison of Dimensionality Reduction Techniques for Pattern Classification. 589-594
• 
  Jörg Bruske, Gerald Sommer: Topology Representing Networks for Intrinsic Dimensionality Estimation. 595-600
• 
  Erkki Häkkinen, Pasi Koikkalainen: SOM Based Visualization in Data Analysis. 601-606
• 
  Gail A. Carpenter, Frank D. M. Wilson: ARTMAP-DS: Pattern Discrimination by Discounting Similarities. 607-612
• 
  Bernd Fritzke: A Self-Organizing Network that Can Follow Non-stationary Distributions. 613-618
• 
  Matthias Burger, Thore Graepel, Klaus Obermayer: Phase Transitions in Soft Topographic Vector Quantization. 619-624
• 
  J. Michael Herrmann, Thomas Villmann: Vector Quantization by Optimal Neural Gas. 625-630
• 
  Jean-Claude Fort, Gilles Pagès: Convergences of the Kohonen Maps: A Dynamical System Approach. 631-636
• 
  Jorma Laaksonen: Local Subspace Classifier. 637-642
• 
  Jean Pierre Delmas: Asymptotic Distributions Associated to Unsupervised Oja's Learning Equation. 643-648
• 
  Nikos A. Vlassis, Apostolos Dimopoulos, George K. Papakonstantinou: The Probabilistic Growing Cell Structures Algorithm. 649-654
• 
  Sepp Hochreiter, Jürgen Schmidhuber: Unsupervised Coding with LOCOCODE. 655-660
• 
  Björn Dobrzewski, D. Ruwish, Mathias Bode: Wave Propagation in Self-Organizing Feature Maps as a Means for the Representation of Temporal Sequences. 661-666
• 
  Nicolas Pican: Contextual Kohonen SOM with Orthogonal Weight Estimator Principle. 667-672

Part 5: Robotics, Adaptive Autonomous Agents, and Control

• 
  Helge Ritter: Self-Organizing Maps for Robot Control. 675-684
• 
  Inman Harvey: Cognition is Not Computation; Evolution is Not Optimisation. 685-690
• 
  Christian Scheier, Rolf Pfeifer: Information Theoretic Implications of Embodiment for Neural Network Learning. 691-696
• 
  Jun Tani: Visual Attention and Learning of a Cognitive Robot. 697-702
• 
  Steffen Egner, Christian Scheier: Feature Binding Through Temporally Correlated Neural Activity in a Robot Model of Visual Perception. 703-708
• 
  Susanne A. Huber, Heinrich H. Bülthoff: Modeling Obstacle Avoidance Behavior of Files Using an Adaptive Autonomous Agent. 709-714
• 
  Titus R. Neumann, Susanne A. Huber, Heinrich H. Bülthoff: Minimalistic Approach to 3D Obstacle Avoidance Behavior from Simulated Evolution. 715-720
• 
  Jari Vaario, Katsunori Shimohara: Synthesis of Developmental and Evolutionary Modeling of Adaptive Autonomous Agents. 721-726
• 
  Andreas Bühlmeier, P. Steiner, Markus L. Rossmann, Karl Goser, Gerhard Manteuffel: Hebbian Multilayer Network in a Wheelchair Robot. 727-732
• 
  Stefano Nolfi, Domenico Parisi: Neural Networks in an Artificial Life Perspective. 733-737
• 
  José del R. Millán: Incremental Acquisition of Local Networks for the Control of Autonomous Robots. 739-744
• 
  Henrik Hautop Lund: Robot-Animal Interaction. 745-750
• 
  Hanspeter A. Mallot, Matthias O. Franz, Bernhard Schölkopf, Heinrich H. Bülthoff: The View-Graph Approach to Visual Navigation and Spatial Memory. 751-756
• 
  Olivier Trullier, Jean-Arcady Meyer: Place Sequence Learning for Navigation. 757-762
• 
  Aude Billard, Gillian Hayes: Learning to Communicate Through Imitation in Autonomous Robots. 763-768
• 
  Rafal Salustowicz, Marco Wiering, Jürgen Schmidhuber: On Learning Soccer Strategies. 769-774
• 
  Kentaro Mizutani, Takashi Omori: A Model of Logic Like Inference by Memory Model PATON. 775-780
• 
  Nadia Saadia, Yassine Amirat, Jean Pontnaut, Amar Ramdane-Cherif: Force Feedback Control of an Assembly Robot by Neural Networks. 781-786
• 
  M. Dapper, R. Maass, V. Zahn, Rolf Eckmiller: Neural Force Control (NFC) for Complex Manipulator Tasks. 787-792
• 
  Thomas Frontzek, Nils Goerke, Rolf Eckmiller: A Hybrid Path Planning System Combining the A^*-Method and RBF-Networks^*. 793-798
• 
  Antonio Chella, Salvatore Gaglio, V. Mulia, Giuseppe Sajeva: An ASSOM Neural Network to Represent Actions Performed by an Autonomous Agent. 799-804
• 
  Ralf Salomon: The Application of Radial Basis Function Networks with Implicit Continuity Constraints. 805-810
• 
  Giacomo Indiveri, Paul F. M. J. Verschure: Autonomous Vehicle Guidance Using Analog VLSI Neuromorphic Sensors. 811-816
• 
  V. Ortmann, Rolf Eckmiller: Neural Network Visual Tracking System. 817-822
• 
  Frank Pasemann: Pole-Balancing with Different Evolved Neurocontrollers. 823-829
• 
  Igor Kokcharov: Calibration of Parallel Robots by Evolutionary Algorithm. 831-836
• 
  Ignacy Culeba, Robert Muszynski: On Use of ANNs to Model and to Control Robot Manipulators. 837-842
• 
  Corinne Ledoux, François Bonnard: Identification of the Electric Arc of a Furnace. 843-848
• 
  Christina Breining, Gerrit Alt: On Using MLPs for Step Size Control in Echo Cancellation for Hands-Free Telephone Sets. 849-854
• 
  Habtom W. Ressom, Lothar Litz: Neurocontrol of Nonlinear Dynamic Systems Subject to Unmeasured Disturbance Inputs. 855-860
• 
  Hugo Zaragoza, Patrick Gallinari: Multiple Multivariate Regression and Global Optimization in a Large Scale Thermodynamical Application. 861-866
• 
  Xavier Desforges, Abdallah Habbadi: A Neural Network for Parameter Estimation of a DC Motor for Feed-Drives. 867-872

Part 6: Speech, Vision, and Pattern Recognition

• 
  Hervé Bourlard: State-of-the-Art and Recent Progress in Hybrid HMM/ANN Speech Recognition. 875-884
• 
  Stephen Grossberg: Perceptual Grouping and Attention During Cortical Form and Motion Processing. 885-894
• 
  Ladan Shams, Christoph von der Malsburg: Development of Shape Primitives from Images of Composite Objects Represented by Complex Cells. 895-900
• 
  Rolf P. Würtz, Tino Lourens: Corner Detection in Color Images by Multiscale Combination of End-Stopped Cortical Cells. 901-906
• 
  Rolf D. Henkel: Constructing the Cyclopean View. 907-912
• 
  Dietmar Heinke, Glyn W. Humphreys: SAIM: A Model of Visual Attention and Neglect. 913-918
• 
  Fred Henrik Hamker, Horst-Michael Gross: Object Selection with Dynamic Neural Maps. 919-924
• 
  Fan Yang, Michel Paindavoine, Hervé Abdi: A Pre-Processing Technique Based on the Wavelet Transform for Linear Autoassociators with Applications to Face Recognition. 925-930
• 
  Kunihiko Fukushima, Hideki Hashimoto: Recognition and Segmentation of Components of a Face by a Multi-Resolution Neural Network. 931-936
• 
  Erol Gelenbe, Taskin Koçak, Leslie M. Collins: Sensor Fusion for Mine Detection with the RNN. 937-942
• 
  Toshifumi Fujita, Hiroshi Ando: Image Segmentation for 3D Object Recognition Using Bidirectional Networks. 943-948
• 
  Stefan Winkler, Patrick Wunsch, Gerd Hirzinger: A Feature Map Approach to Pose Estimation Based on Quaternions. 949-954
• 
  Axel Christian Varchmin, Robert Rae, Helge Ritter: Facial Feature Detection Using Neural Networks. 955-960
• 
  Hakan Bakircioglu, Erol Gelenbe, Lawrence Carin: Random Neural Network Recognition of Shaped Objects in Strong Clutter. 961-966
• 
  Holger Schwenk, Yoshua Bengio: AdaBoosting Neural Networks: Application to on-line Character Recognition. 967-972
• 
  Urs-Viktor Marti, Guido Kaufmann, Horst Bunke: Cursive Script Recognition with Time Delay Neural Networks Using Learning Hints. 973-978

Part 7: Prediction, Forecasting, and Monitoring

• 
  Eric de Bodt, Philippe Grégoire, Marie Cottrell: A Powerful Tool for Fitting and Forecasting Deterministic and Stochastic Processes: The Kohonen Classification. 981-986
• 
  Morgan Mangeas: Neural Model Selection: How to Determine the Fittest Criterion? 987-992
• 
  Marie Cottrell, Bernard Girard, Patrick Rousset: Long Term Forecasting by Combining Kohonen Algorithm and Standard Prevision. 993-998
• 
  Klaus-Robert Müller, Alex J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik: Predicting Time Series with Support Vector Machines. 999-1004
• 
  Thomas Burg, Nadine N. Tschichold-Gürman: An Extended Neuron Model for Efficient Time-Series Generation and Prediction. 1005-1010
• 
  Myriam Monteyne, Tristan Salomé, Françoise de Viron, Jean-Michel Renders, Pierre Doulliez, François Dongier, Jean Claus: Different Model Types for Short-Term Forecasting of Characteristic Load Points. 1011-1016
• 
  José Nuno Fidalgo, Manuel A. Matos, Maria Teresa de Ponce Leão: Assessing Error Bars in Distribution Load Curve Estimation. 1017-1022
• 
  Thomas Ragg, Steffen Gutjahr: Building High Performant Classifiers by Integrating Bayesian Learning, Mutual Information and Committee Techniques - A Case Study in Time Series Prediction. 1023-1028
• 
  Thomas Czernichow, Antonio Muñoz: A Probability Estimation Based Criteria for Model Evaluation. 1029-1034
• 
  Francesco Camastra, Anna Maria Colla: Short-Term Load Forecasting Based on Correlation Dimension Estimation and Neural Nets. 1035-1040
• 
  Thierry Lenez, Bernadette Dorizzi: Predictive Neural Models in Noisy Environment. 1041-1046
• 
  Ashraf A. M. Khalaf, Kenji Nakayama, Kazuyuki Hara: A Neural-FIR Predictor: Minimum Size Estimation Based on Nonlinearity Analysis of Input Sequence. 1047-1052
• 
  Dirk Husmeier, John G. Taylor: Modeling Conditional Probabilities with Committees of RVFL Networks. 1053-1058
• 
  Bernhard Sick: Classifying the Wear of Turning Tools with Neural Networks. 1059-1064
• 
  Yves Moreau, Herman Verrelst, Joos Vandewalle: Detection of Mobile Phone Fraud Using Supervised Neural Networks: A First Prototype. 1065-1070
• 
  Arto Visala, Hannu Pitkänen, Aarne Halme: Wiener Type SOM- and MLP-classifiers for Recognition of Dynamic Modes. 1071-1076
• 
  Jens Kohlmorgen, Klaus-Robert Müller, J. Rittweger, Klaus Pawelzik: Analysis of Wake/Sleep EEG with Competing Experts. 1077-1082
• 
  Rosaria Silipo, Gustavo Deco, Rossano Vergassola, Christian Schittenkopf, Celio Gremigni: Nonlinear Modelling of the Daily Heart Rhythm. 1083-1088
• 
  Younès Bennani, Fabrice Bossaert, Elisabeth Didelet: Linear and Nonlinear Combinations of Connectionist Models for Local Diagnosis in Real-Time Telephone Network Traffic Management. 1089-1094
• 
  Olivier Gérard, Jean-Noël Patillon, Florence d'Alché-Buc: Neural Network Adaptive Modeling of Battery Discharge Behavior. 1095-1100
• 
  Rainer Müller: Neural Combustion Control. 1101-1106
• 
  Yasmine Assef, Patrick Bastard, Michel Meunier: A Neural Network Based Fault Detector for Power Distribution Systems. 1107-1112
• 
  Edmund Handschin, Dietmar Kuhlmann, Christian Rehtanz: Visualization and Analysis of Voltage Stability Using Self-Organizing Neural Networks. 1113-1118
• 
  J. Ambühl, D. Cattani, P. Eckert: Classification of Meteorological Patterns. 1119-1124
• 
  Mikhail F. Kanevski, Vasiliy V. Demyanov, Michel Maignan: Mapping of Soil Contamination by Using Artificial Neural Networks and Multivariate Geostatistics. 1125-1130

Part 8: Implementations

• 
  Eric A. Vittoz: Pseudo-Resistive Networks and their Applications to Analog Collective Computation. 1133-1150
• 
  Tamás Roska: Implementation of CNN Computing Technology. 1151-1155
• 
  Tzi-Dar Chiueh, Linkai Bu: Implementation of a Masking Network for Speech Perception. 1157-1162
• 
  Rainer A. Deutschmann, Charles M. Higgins, Christof Koch: Real-Time Analog VLSI Sensors for 2-D Direction of Motion. 1163-1168
• 
  Chang-Han Yi, Robert Schlabbach, Holger Kroth, Heinrich Klar: An Improved Multiplexed Resistive Network for Analog Image Preprocessing. 1169-1174
• 
  Giacomo M. Bisio, Gian Marco Bo, M. Confalone, Luigi Raffo, Silvio P. Sabatini, M. P. Zizola: An Analog VLSI Computational Engine for Early Vision Tasks. 1175-1180
• 
  Michael Becker, Rolf Eckmiller: Spatio-temporal Filter Adjustment from Evaluative Feedback for a Retina Implant. 1181-1186
• 
  Axel Jahnke, Tim Schönauer, Ulrich Roth, K. Mohraz, Heinrich Klar: Simulation of Spiking Neural Networks on Different Hardware Platforms. 1187-1192
• 
  Tadeusz Lobos, Andrzej Cichocki, Pawel Kostyla, Zbigniew Waclawek: Adaptive On-line Learing Algorithm for Robust Estimation of Parameters of Noisy Sinusoidal Signals. 1193-1198
• 
  Juan Manuel Moreno, Jordi Madrenas, Eduard Alarcón, Joan Cabestany: Analog Sequential Architecture for Neuro-Fuzzy Models VLSI Implementation. 1199-1204
• 
  M. Oláh, P. Masa, András Lörincz: A Mixed-Signal VLSI Circuit for Skeletonization by Grassfire Transformation. 1205-1210
• 
  Jean-Denis Muller, Ph. Cheynet, Raoul Velazco: Analysis and Improvement of Neural Network Robustness for On-Board Satellite Image Processing. 1211-1216
• 
  Ulrich Roth, Axel Jahnke, Heinrich Klar: On-Line Hebbian Learning for Spiking Neurons: Architecture of the Weight-Unit of NESPINN. 1217-1222
• 
  Eduard Säckinger: Measurement of Finite-Precision Effects in Handwriting- and Speech-Recognition Algorithms. 1223-1228
• 
  Daniela Baratta, Gian Marco Bo, Daniele D. Caviglia, Maurizio Valle, Giovanni Canepa, Riccardo Parenti, Carla Penno: A Hardware Implementation of Hierarchical Neural Networks for Real-Time Quality Contol Systems in Industrial Applications. 1229-1234
• 
  Thomas Fischer, Wolfgang Eppler, Hartmut Gemmeke, Gerd Kock, Thomas Becher: The SAND Neurochip and Its Embedding in the MiND System. 1235-1240
• 
  Markus L. Rossmann, Andreas Bühlmeier, Gerhard Manteuffel, Karl Goser: Short- and Long-Term Dynamics in a Stochastic Pulse Stream Neuron Implemented in FPGA. 1241-1246
• 
  Andrés Pérez-Uribe, Eduardo Sanchez: FPGA Implementation of a Network of Neuronlike Adaptive Elements. 1247-1252
• 
  I. Saxena, P. Moerland, Emile Fiesler, A. Pourzand: Handwritten Digit Recognition with Binary Optical Perceptron. 1253-1258
• 
  Pasi Kolinummi, Timo Hämäläinen, Jukka Saarinen: Mapping of Radial Basis Function Networks to Partial Tree Shape Parallel Neurocomputer. 1259-1264
• 
  Paolo Del Giudice, Stefano Fusi: Attractor Dynamics in an Electronic Neural Network. 1265-1270

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