CiNii Books - Artificial neural networks : ICANN '97 : 7th International Conference, Lausanne, Switzerland, October 8-10, 1997 : proceedings

This book constitutes the refereed proceedings of the 7th International Conference on Artificial Neural Networks, ICANN'97, held in Lausanne, Switzerland,in October 1997. The 201 revised papers presented were selected from a large number of submissions and give a unique documentation of the state of the art in the area. The papers are organized in parts on coding and learning in biology; cortical maps and receptive fields; learning: theory and applications; signal processing: blind source separation, vector quantization, and self-organization; robotics, autonomous agents, and control; speech, vision and pattern recognition; prediction, forecasting and monitoring; and implementations.

Table of Contents

Reward responses of dopamine neurons: A biological reinforcement signal.- The information content of action potential trains a synaptic basis.- Cortical cell assemblies, laminar interaction, and thalamocortical interplay.- Cross-correlations in sparsely connected recurrent networks of spiking neurons.- A comparative study of pattern detection algorithm and dynamical system approach using simulated spike trains.- Spatio-temporal pattern recognition with neural networks: Application to speech.- Noise in integrate-and-fire models of neuronal dynamics.- Coarse coding accounts for improvement of spatial discrimination after plastic reorganization in rats and humans.- Analogue resolution in a model of the Schaffer collaterals.- Modeling networks with linear (VLSI) integrate-and-fire neurons.- An information-theoretic analysis of temporal coding strategies by spiking central neurons.- Correlation coding in stochastic neural networks.- Two-dimensional Hodgkin-Huxley equations for investigating a basis of pulse-processing neural networks.- Concurrent parallel-sequential processing in gamma controlled cortical-type networks of spiking neurones.- A noise-robust auditory modelling front end for voiced speech.- A novelty detector using a network of integrate and fire neurons.- Derivation of pool dynamics from microscopic neuronal models.- How a single Purkinje cell could learn the adaptive timing of the classically conditioned eye-blink response.- An algorithm for synaptic modification based on exact timing of pre- and post-synaptic action potentials.- Modelling plasticity in rat barrel cortex induced by one spared whisker.- Mathematical analysis of competition between sensory ganglion cells for nerve growth factor in the skin.- Competition amongst neurons for neurotrophins.- Implementing hebbian learning in a rank-based neural network.- A model of clipped hebbian learning in a neocortical pyramidal cell.- Hebbian delay adaptation in a network of integrate-and-fire neurons.- Hippocampal formation trains independent components via forcing input reconstruction.- Nature vs. nurture in the development of tangential connections and functional maps in the visual cortex.- Geometric relationships between feature maps in cat visual cortex.- A linear hebbian model for the development of spatiotemporal receptive fields of simple cells.- Synapse clustering can drive simultaneous ON-OFF and ocular-dominance segregation in a model of area 17.- Must pinwheels move during visual development ?.- Extending the TRN model in a biologically plausible way.- SOM-Model for the development of oriented receptive fields and orientation maps from non-oriented ON-center OFF-center inputs.- On the anatomical basis of field size, contrast sensitivity, and orientation selectivity in macaque striate cortex: A model study.- Statistics of natural and urban images.- A CBL network model with intracortical plasticity and natural image stimuli.- Geometry of orientation preference map determines nonclassical receptive field properties.- A model for orientation tuning and contextual effects of orientation selective receptive fields.- Objective functions for neural map formation.- Relative time scales in the self-organization of pattern classification: From "one-shot" to statistical learning.- Realization of geometric illusions and geometry of visual space with neural networks.- The Support Vector method.- On the significance of Markov decision processes.- Economical reinforcement learning for non stationary problems.- A double gradient algorithm to optimize regularization.- Global least-squares vs. EM training for the Gaussian mixture of experts.- Accelerated learning in Boltzmann Machines using mean field theory.- Adaptive online learning for nonstationary problems.- Weight discretization due to optical constraints and its influence on the generalization abilities of a simple perceptron.- Wavelet frames based estimator.- A spatio-temporal perceptron for on-line handwritten character recognition.- Learning oscillations using adaptive control.- Creation of neural networks based on developmental and evolutionary principles.- A boosting algorithm for regression.- Combining regularized neural networks.- Making stochastic networks deterministic.- Unsupervised learning in networks of spiking neurons using temporal coding.- Experiments on regularizing MLP models with background knowledge.- Elliptical basis function networks for classification tasks.- Probabilistic Neural Networks with rotated kernel functions.- Statistical control of RBF-like networks for classification.- Improving RBF networks by the feature selection approach EUBAFES.- Polynomial classifiers and support vector machines.- Unique representations of dynamical systems produced by recurrent neural networks.- Generalization of Elman networks.- Designing neural networks by a combination of structural learning and genetic algorithms.- A recurrent self-organizing map for temporal sequence processing.- An extended Elman net for modeling time series.- Recurrent associative memory network of nonlinear coupled oscillators.- A layered recurrent neural network for feature grouping.- A multilayer real-time, recurrent learning algorithm for improved convergence.- Increasing the capacity of a hopfield network without sacrificing functionality.- A novel associative network accommodating pattern deformation.- Adaptive noise injection for input variables relevance determination.- Input selection with partial retraining.- On the complexity of recognizing iterated differences of polyhedra.- Optimal linear regression on classifier outputs.- Learning verification in multilayer neural networks.- Design of a fault tolerant multilayer perceptron with a desired level of robustness.- Mixtures of experts estimate a posteriori probabilities.- Admissibility and optimality of the cascade-correlation algorithm.- The effective VC dimension of the n-tuple classifier.- From neural principal components to neural independent components.- Entropy optimization.- Improving the performance of infomax using statistical signal processing techniques.- A maximum likelihood approach to nonlinear blind source separation.- A perceptron-based approach to piecewise linear modeling with an application to time series.- Local independent component analysis by the self-organizing map.- Model breaking detection using independent component classifier.- Neural network based processing for smart sensors arrays.- Application of the MEC network to principal component analysis and source separation.- Semi-blind source parameter separation.- Kernel principal component analysis.- An empirical comparison of dimensionality reduction techniques for pattern classification.- Topology representing networks for intrinsic dimensionality estimation.- SOM based visualization in data analysis.- ARTMAP-DS: pattern discrimination by discounting similarities.- A self-organizing network that can follow non-stationary distributions.- Phase transitions in soft topographic vector quantization.- Vector quantization by optimal neural gas.- Convergences of the Kohonen maps: a dynamical system approach.- Local Subspace Classifier.- Asymptotic distributions associated to unsupervised Oja's learning equation.- The probabilistic growing cell structures algorithm.- Unsupervised coding with lococode.- Wave propagation in self-organizing feature maps as a means for the representation of temporal sequences.- Contextual kohonen SOM with orthogonal weight estimator principle.- Self-organizing maps for robot control.- Cognition is not computation
Evolution is not optimisation.- Information theoretic implications of embodiment for neural network learning.- Visual attention and learning of a cognitive robot.- Feature binding through temporally correlated neural activity in a robot model of visual perception.- Modeling obstacle avoidance behavior of flies using an adaptive autonomous agent.- Minimalistic approach to 3D obstacle avoidance behavior from simulated evolution.- Synthesis of developmental and evolutionary modeling of adaptive autonomous agents.- Hebbian multilayer network in a wheelchair robot.- Neural networks in an artificial life perspective.- Incremental acquisition of local networks for the control of autonomous robots.- Robot-animal interaction.- The view-graph approach to visual navigation and spatial memory.- Place sequence learning for navigation.- Learning to communicate through imitation in autonomous robots.- On learning soccer strategies.- A model of logic like inference by memory model PATON.- Force feedback control of an assembly robot by neural networks.- Neural force control (NFC) for complex manipulator tasks.- A hybrid path planning system combining the A*-method and RBF-networks.- An ASSOM neural network to represent actions performed by an autonomous agent.- The application of radial basis function networks with implicit continuity constraints.- Autonomous vehicle guidance using analog VLSI neuromorphic sensors.- Neural network visual tracking system.- Pole-balancing with different evolved neurocontrollers.- Calibration of parallel robots by evolutionary algorithm.- On use of ANNs to model and to control robot manipulators.- Identification of the electric arc of a furnace.- On using MLPs for step size control in echo cancellation for hands-free telephone sets.- Neurocontrol of nonlinear dynamic systems subject to unmeasured disturbance inputs.- Multiple multivariate regression and global optimization in a large scale thermodynamical application.- A neural network for parameter estimation of a DC motor for feed-drives.- State-of-the-art and recent progress in hybrid HMM/ANN speech recognition.- Perceptual grouping and attention during cortical form and motion processing.- Development of shape primitives from images of composite objects represented by complex cells.- Corner detection in color images by multiscale combination of end-stopped cortical cells.- Constructing the cyclopean view.- SAIM: A model of visual attention and neglect.- Object selection with dynamic neural maps.- A pre-processing technique based on the wavelet transform for linear autoassociators with applications to face recognition.- Recognition and segmentation of components of a face by a multi-resolution neural network.- Sensor fusion for mine detection with the RNN.- Image segmentation for 3D object recognition using bidirectional networks.- A feature map approach to pose estimation based on quaternions.- Facial feature detection using neural networks.- Random neural network recognition of shaped objects in strong clutter.- AdaBoosting neural networks: Application to on-line character recognition.- Cursive script recognition with time delay neural networks using learning hints.- A powerful tool for fitting and forecasting deterministic and stochastic processes: The Kohonen classification.- Neural model selection: How to determine the fittest criterion?.- Long term forecasting by combining Kohonen algorithm and standard prevision.- Predicting time series with support vector machines.- An extended neuron model for efficient timeseries generation and prediction.- Different model types for short-term forecasting of characteristic load points.- Assessing error bars in distribution load curve estimation.- Building high performant classifiers by Integrating bayesian learning, mutual Information and committee techniques - A case study in time series prediction -.- A probability estimation based criteria for model evaluation.- Short-term load forecasting based on correlation dimension estimation and neural nets.- Predictive neural models in noisy environment.- A Neural-FIR predictor: Minimum size estimation based on nonlinearity analysis of input sequence.- Modelling conditional probabilities with committees of RVFL networks.- Classifying the wear of turning tools with neural networks.- Detection of mobile phone fraud using supervised neural networks: A first prototype.- Wiener type SOM-and MLP-Classifiers for recognition of dynamic modes.- Analysis of wake/sleep EEG with competing experts.- Nonlinear modelling of the daily heart rhythm.- Linear and nonlinear combinations of connectionist models for local diagnosis in real-time telephone network traffic management.- Neural network adaptive modeling of battery discharge behavior.- Neural combustion control.- A neural network based fault detector for power distribution systems.- Visualization and analysis of voltage stability using self-organizing neural networks.- Classification of meteorological patterns.- Mapping of soil contamination by using artificial neural networks and multivariate geostatistics.- Pseudo-resistive networks and their applications to analog collective computation.- Implementation of CNN computing technology.- Implementation of a masking network for speech perception.- Real-time analog VLSI sensors for 2-D direction of motion.- An improved multiplexed resistive network for analog image preprocessing.- An analog VLSI computational engine for early vision tasks.- Spatio-temporal filter adjustment from evaluative feedback for a retina implant.- Simulation of spiking neural networks on different hardware platforms.- Adaptive on-line learning algorithm for robust estimation of parameters of noisy sinusoidal signals.- Analog sequential architecture for neuro-fuzzy models VLSI implementation.- A mixed-signal VLSI circuit for skeletonization by grassfire transformation.- Analysis and improvement of neural network robustness for on-board satellite image processing.- On-line Hebbian learning for spiking neurons: Architecture of the weight-unit of NESPINN.- Measurement of finite-precision effects in handwriting- and speech-recognition algorithms.- A hardware implementation of hierarchical Neural Networks for real-time quality control systems in industrial applications.- The SAND neurochip and its embedding in the MiND system.- Short- and long-term dynamics in a stochastic pulse stream neuron implemented in FPGA.- FPGA implementation of a network of neuronlike adaptive elements.- Handwritten digit recognition with binary optical perceptron.- Mapping of radial basis function networks to partial tree shape parallel neurocomputer.- Attractor dynamics in an electronic neural network.

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Artificial neural networks : ICANN '97 : 7th International Conference, Lausanne, Switzerland, October 8-10, 1997 : proceedings

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