ICANN 98. Proceedings of the 8th International Conference on Artificial Neural Networks, Skovde, Sweden, 2-4 September 1998. Volume 1. Perspectives in Neural Computing

Niklasson, L, et al., eds.

ISBN 10: 3540762639 / ISBN 13: 9783540762638

Editore: Springer, 1998

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Dati bibliografici

• Titolo: ICANN 98. Proceedings of the 8th International Conference on Artificial Neural Networks, Skovde, Sweden, 2-4 September 1998. Volume 1. Perspectives in Neural Computing
• Editore: Springer
• Data di pubblicazione: 1998
• Lingua: Inglese
• ISBN 10: 3540762639
• ISBN 13: 9783540762638
• Rilegatura: Brossura
• Condizione: Good

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Riassunto

ICANN, the International Conference on Artificial Neural Networks, is the official conference series of the European Neural Network Society which started in Helsinki in 1991. Since then ICANN has taken place in Brighton, Amsterdam, Sorrento, Paris, Bochum and Lausanne, and has become Europe's major meeting in the field of neural networks. This book contains the proceedings of ICANN 98, held 2-4 September 1998 in Skovde, Sweden. Of 340 submissions to ICANN 98, 180 were accepted for publication and presentation at the conference. In addition, this book contains seven invited papers presented at the conference. A conference of this size is obviously not organized by three individuals alone. We therefore would like to thank the following people and organizations for supporting ICANN 98 in one way or another: • the European Neural Network Society and the Swedish Neural Network Society for their active support in the organization of this conference, • the Programme Committee and all reviewers for the hard and timely work that was required to produce more than 900 reviews during April 1998, • the Steering Committee which met in Skovde in May 1998 for the final selection of papers and the preparation of the conference program, • the other Module Chairs: Bengt Asker (Industry and Research), Harald Brandt (Applications), Anders Lansner (Computational Neuroscience and Brain Theory), Thorsteinn Rognvaldsson (Theory), Noel Sharkey (co­ chair Autonomous Robotics and Adaptive Behavior), Bertil Svensson (Hardware and Implementations), • the conference secretary, Leila Khammari, and the rest of the

Contenuti

Invited Presentations.- (Back) Towards Diagrammatic Representation and Reasoning in a Connectionist Framework.- Variational Learning in Graphical Models and Neural Networks.- Synchronization: The Computational Currency of Cognition.- Applications of Vapnik’s Theory for Prediction.- Brains, Gases and Robots.- Self-Organization of Very Large Document Collections: State of the Art.- Silicon Artificial Neural Networks.- Oral Presentations: Theory: Theory I: Algorithms.- Efficient Top-Down Jacobian Evaluation of Tree-Structured Neural Networks.- Tractable Undirected Approximations for Graphical Models.- Convex Cost Functions for Support Vector Regression.- Asymptotically Optimal Choice of ?-Loss for Support Vector Machines.- Support Vector Regression with Automatic Accuracy Control.- Theory II: Dynamical systems, Time Series.- Queuing Theory for Spike Driven Synaptic Dynamics.- The Deformable Feature Map — Adaptive Plasticity for Function Approximation.- Asymptotic Behavior of a Neural Network with Dynamic External Input.- Theory III: Signal Decomposition Methods.- Independent Component Analysis for Time-Dependent Stochastic Processes.- Denoising of Sensory Data by Maximum Likelihood Estimation of Sparse Components.- Kernel PCA Pattern Reconstruction via Approximate Pre-Images.- The Pearson Mixture Model for Cluster Analysis and Data Visualisation.- Theory IV: Learning Theory.- Why Feed-Forward Networks are in a Bad Shape.- Transients and Asymptotics of Natural Gradient Learning.- An Analysis of Convergence in Generalized LVQ.- Ultrametric Structure in Autoencoder Error Surfaces.- The Dynamics of Matrix Momentum.- Dynamics of Batch Learning in Multilayer Neural Networks.- An Asymptotic Analysis of AdaBoost in the Binary Classification Case.- Least Absolute Shrinkage is Equivalent to Quadratic Penalization.- Oral Presentations: Applications: Applications I: Process Control, Diagnosis.- Neural Network Modelling of Ore Grade Spatial Variability.- Neural Virtual Sensors — Estimation of Combustion Quality in SI Engines Using the Spark Plug.- Real-Time Ion Temperature Profiles in the JET Nuclear Fusion Experiment.- Detection of Spatio-Temporal Ultrasonic Transient Families Using Filter Banks and Neural Nets.- Applications II: Image Processing.- Object Recognition with Multiple Feature Types.- Learning Gestures with Time-Delay RBF Networks.- Comparison of Adaptive Strategies for On-Line Character Recognition.- A Binary Correlation Matrix Memory k-NN Classifier.- Applications III: Speech, Telecom, Finance.- Multinet: A New Connectionist Architecture for Speech Recognition.- Simulation Support and ATM Performance Prediction.- TDNN Approach to Measuring Raindrop Sizes and Velocities.- Optimizing the Evidence.- Applications IV: Medicine, Sequence Analysis.- Adapting an Ensemble Approach for the Diagnosis of Breast Cancer.- Independent Component Analysis in Wave Decomposition of Auditory Evoked Fields.- Experiments in Gait Pattern Classification with Neural Networks of Adaptive Architecture.- Using Feature Selection to Find Inputs that Work Better as Extra Outputs.- Applications V: Hybrid Systems, General Techniques.- Analysis of Multi-Choice Questionnaires Through Self-Organizing Maps.- A Niching Genetic Algorithm for Selecting Features for Neural Network Classifiers.- The Wavelet Transform for Time Series Prediction.- Empirical Evaluation of Bayesian Sampling for Neural Classifiers.- Oral Presentations: Computational Neuroscience and Brain Theory.- State-Dependent Spatio-Temporal Restructuring of Receptive Fields in the Primary Visual Pathway.- Frequency Spectrum of Coupled Stochastic Neurons with Refractoriness.- Analysing the Context Dependence of Receptive Fields in Visual Cortex.- A Neural Model of Stereopsis.- Continuous Dynamics of Neuronal Delay Adaptation.- The Critical Synaptic Number for Rhythmogenesis and Synchronization in a Network Model of the Cerebellar Granular Layer.- A Model of Cortical Plasticity: Integration and Segregation Based on Temporal Input Patterns.- Self-Organisation and Cortical Dynamics.- Oral Presentations: Connectionist Cognitive Science and Artificial Intelligence.- Continuous Time Recurrent Neural Networks for Grammatical Induction.- Encoding Structure in Boolean Space.- Non-Compositional Representation in Connectionist Networks.- A Connectionist Model for Categorical Perception and Symbol Grounding.- Enriched Lexical Representations, Large Corpora, and the Performance of SRNs.- Oral Presentations: Autonomous Robotics and Adaptive Behavior.- Using Focus to Direct Environmental Mapping.- A Biologically Inspired Adaptive Control Architecture Based on Neural Networks for a Four-Legged Walking Machine.- 2-D Pole Balancing with Recurrent Evolutionary Networks.- GripSee: A Robot for Visually-Guided Grasping.- Dynamics of a Classical Conditioning Model.- CMAC Models Learn to Play Soccer.- Pseudo-Parametric Q-Learning Using Feedforward Neural Networks.- Continuous Q-Learning Resource Allocation Network.- Oral Presentations: Hardware and Implementations.- Sparse Distributed Memory Mapping on Partial Tree Shape Neurocomputer.- PRESENCE, a Hardware Implementation of Binary Neural Networks.- Analog VLSI Implementation of a Spike Driven Stochastic Dynamical Synapse.- Neural Dynamics in Real-Time for Large Scale Biomorphic Neural Networks.- Contents, Volume 2: Poster Presentations Poster Presentations: Theory Spotlight Presentations: Theory I: Algorithms.- A Study on Functional-Link Neural Units with Maximum Entropy Response.- Mean Field Theory Based on Belief Networks for Approximate Inference.- On the Use of Local RBF Networks to Approximate Multivalued Functions and Relations.- Learning Higher Order Boltzmann Machinces Using Linear Response.- Order Parameters for Self-Organizing Maps.- Slope Centering: Making Shortcut Weights Effective.- Spotlight Presentations: Theory II: Dynamical Systems, Time Series.- Constrained Second-Order Recurrent Networks for Finite-State Automata Induction.- Exact Learning Curves for EKF Training.- Spotlight Presentation: Theory IH: Signal Decomposition Methods.- Sparse Regression: Utilizing the Higher-Order Structure of Data for Prediction.- Poster Session I: Theory.- A Linear Programming Neural Circuit Model.- Learning Invariance Manifolds.- Developmental Evolution of an Edge Detecting Retina.- Activity Driven Update in the Neural Abstraction Pyramid.- Jacobian Neural Network Learning Algorithms.- Quadratic Concepts.- Complexity of Boolean Computations for a Spiking Neuron.- Unsupervised Time Series Segmentation by Predictive Modular Neural Networks.- ICE — An Incremental Hybrid System for Continuous Learning.- Synthesis of Probabilistic Automata in pRAM Neural Networks.- Neural Modeling of Nonlinear Differential Equations with Discrete Measurements A Lagrangian Approach.- Simple Synchrony Networks: Learning to Parse Natural Language with Temporal Synchrony Variable Binding.- Gaussian Processes for Switching Regimes.- Artificial Neural Networks as Approximators of Stochastic Processes.- Piecewise Affine Neural Networks and Nonlinear Control.- Poster Session II: Theory.- Some Complexity Results for Perceptron Networks.- Multilayer Neural Networks for Classification: A Pedagogical Theorem.- An Experimental Comparison of Neural ICA Algorithms.- The Principal Independent Components of Images.- Pattern Formation in Locally Connected Oscillatory Networks.- LOCOCODE versus PCA and ICA.- TDSEP — An Efficient Algorithm for Blind Separation Using Time Structure.- Optimal Cross-Validation Split Ratio: Experimental Investigation.- On the Convergence Properties of the Temporal Kohonen Map and the Recurrent Self-Organizing Map.- Multivariate Linear Regression on Classifier Outputs: A Capacity Study.- Poster Presentations: Applications Spotlight Presentations: Applications I: Process Control, Diagnosis.- Automated Statistical Recognition of Partial Discharges in Insulation Systems.- A Radar System with Phase-Sensitive Millimetric Wave Circuitry and Complex-Amplitude Neural Processing.- Chances and Risks of Sensor Fusion with Neural Networks: An Application Example.- Support Objects for Domain Approximation.- A Comparison of Traditional and Soft-Computing Methods in a Real-Time Control Application.- Spotlight Presentations: Applications II: Image Processing.- Efficient Local Subspace Construction for Neural Data Modeling.- Edge Detection of Multispectral Images Using the 1-D Self-Organizing Map.- Design of Cellular Neural Networks for Binary and Gray Level Image Processing.- Adaptive Illuminant Estimation Using Neural Networks.- Automatic Neural Generalized Font Identification.- Spotlight Presentations: Applications III: Speech, Telecom, Finance.- An Approach to Blin Source Separation of Speech Signals.- Data Fusion for Diagnosis in a Telecommunication Network.- Creating an Order in Distributed Digital Libraries by Integrating Independent Self-Organizing Maps.- Competitive Learning for Binary Valued Data.- Neural Network-Based Inferential Sensing.- Spotlight Presentations: Applications IV: Medicine, Sequence Analysis, Environment.- Retina Encoder Inversion for Retina Implant Simulation.- The Automated Identification of Tubercle Bacilli Using Image Processing and Neural Computing Techniques.- Black-Box Software Sensor Design for Environmental Monitoring.- Classifying Regional Seismic Signals Using TDNN-Alike Neural Networks.- A Hierarchical Self-Organizing Map Model for Sequence Recognition.- Poster Session I: Applications.- Discrete Time Backpropagation and Synaptic Delay Based Artificial Neural Networks in Chaotic Time Series Prediction.- A Learning Method of Fuzzy Inference Rules Using Vector Quantization.- Mixed Fuzzy-System and Artificial Neural Network Approach to the Automated Recognition of Mouth Expressions.- COMVIS: A Communication Framework for Computer Vision.- Implementing a Hybrid Architecture for Artificial Neural Network Applications.- Application of ANN to the Selection of a Valve from the Catalogue.- A Neural Network Approach to Functional MRI Pattern Analysis — Clustering of Time-Series by Hierarchical Vector Quantization.- Penalized Training for Serially Correlated Data.- Poster Session II: Applications.- Gaussian Mixture and Kernel Based Approaches to Blind Separation of Sources Using Neural Nets.- The Adaptive Setback Thermostat.- Architecture Optimization in Feedforward Connectionist Models.- Neural Velocity Force Control for Industrial Manipulators Contacting Rigid Surfaces.- Neural Trajectory Optimization (NTO) for Manipulator Tracking of Unknown Surfaces.- Computer Network User Behaviour Visualisation Using Self Organising Maps.- Neural Control of a Virtual Prosthesis.- Adaptive Clustering and Multidimensional Scaling of Large and High-Dimensional Data Sets.- Behavior of the Weights of a Support Vector Machine as a Function of the Regularization Parameter C.- Convergence Properties of a Modified Temporal Anti-Hebbian Model.- Volatility Prediction with Mixture Density Networks.- Introducing a Clustering Technique into Recurrent Neural Networks for Solving Large-Scale Traveling Salesman Problems.- Poster Presentations: Computational Neuroscience and Brain Theory Spotlight Presentations: Computational Neuroscience and Brain Theory (1).- Comparing Different Measures of Spatio-Temporal Patterns in Neural Activity.- Influence of Recurrent Excitation and Inhibition on Receptive Field Size and Contrast Sensitivity in Layer 4C of Macaque Striate Cortex.- Self-Organization of Shift-Invariant Receptive Fields Through Pre- and Postsynaptic Competition.- A Cortical Interpretation of ASSOMs.- Spotlight Presentations: Computational Neuroscience and Brain Theory (2).- Decoding Population Responses in Short Epochs.- Modeling Reward Dependent Activity Pattern of Caudate Neurons.- Neural Signalling: It’s a Gas.- Fast Learning of Dynamic Compensation in Motor Control.- Poster Session I: Computational Neuroscience and Brain Theory.- A One-Dimensional Frequency Map Implemented Using a Network of Integrate-and-Fire Neurons.- The Role of Spatio-Temporal Neural Response Characteristics in the Formation of Synchrony.- Three-Layered Neural Model Between Cortical Areas VI and IT.- An Interruptible Connectionist Model for Real-Time Pattern Recognition.- Implementation of Tunable Receptive Field (RF) Filters for Learning Retina Implants.- Rate and Temporal Coding with a Neural Oscillator.- Poster Session II: Computational Neuroscience and Brain Theory.- Phase Transitions in Even Cyclic Inhibitory Networks.- The Basal Ganglia Viewed as an Action Selection Device.- Parameters Estimation in the Diffusion Model for Multidimensional Neural Data.- Asynchronous Simulation of Large Networks of Spiking Neurons and Dynamical Synapses.- Novelty Learning in a Discrete Time Chaotic Network.- Spike-Based Hebbian Learning for Stimulus Discrimination.- Poster Presentations: Connectionist Cognitive Science and Artificial Intelligence Spotlight Presentation: Connectionist Cognitive Science and Artificial Intelligence.- What Type of Finite Computations Do Recurrent Neural Networks Perform.- Poster Session I: Connectionist Cognitive Science and Artificial Intelligence.- Statistical Estimation in Conceptual Spaces.- A Connectionist Account of Spanish Determiner Production.- Learning Decompositional Structures in a Network of Max-? Units with Exponents as Connection Strengths.- Fuzzy Heterogeneous Neural Networks for Signal Forecasting.- Poster Presentations: Autonomous Robotics and Adaptive Behavior Spotlight Presentations: Autonomous Robotics and Adaptive Behavior (1).- Behavioural Coordination in Acoustically Coupled Agents.- Self-Localization by Hidden Representations.- Reinforcement Learning of Collision-Free Motions for a Robot Arm with a Sensing Skin.- Multitask Pattern Recognition for Vision-Based Autonomous Robots.- Poster Session II: Autonomous Robotics and Adaptive Behavior.- Three Principles of Hierarchical Task Composition in Reinforcement Learning.- On-Line EM Algorithm and Reinforcement Learning.- Embedding Knowledge in Reinforcement Learning.- Multistage STM in a Multilayer Hebbian Learning Architecture for Local Navigation.- Diploid Robots Adapting to Fast Changing Environments.- Dynamical Adaptation of a Neural-Net Based Agent.- Poster Presentations: Hardware and Implementations Spotlight Presentations: Hardware and Implementations.- A Reconfigurable Neuroprocessor with On-Chip Pruning.- Laser Neural Network Demonstrates Data Switching Functions.- A New Stochastic Learning Algorithm for Analog Hardware Implementation.- An Analog Neural Signal Processor for Embedded Applications.- The NeuroAccess System.- Recognizing Handwritten Digits with a Dedicated Analog VLSI Feature Extractor.- Author Index.- Author Index.