Artificial Neural Networks — ICANN ’97

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.