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Artificial Neural Networks — ICANN'97 : 7th International Conference Lausanne, Switzerland, October 8–10, 1997 Proceeedings

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Cover of 'Artificial Neural Networks — ICANN'97 : 7th International Conference Lausanne, Switzerland, October 8–10, 1997 Proceeedings'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Reward responses of dopamine neurons: A biological reinforcement signal
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    Chapter 2 The information content of action potential trains a synaptic basis
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    Chapter 3 Cortical cell assemblies, laminar interaction, and thalamocortical interplay
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    Chapter 4 Cross-correlations in sparsely connected recurrent networks of spiking neurons
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    Chapter 5 A comparative study of pattern detection algorithm and dynamical system approach using simulated spike trains
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    Chapter 6 Spatio-temporal pattern recognition with neural networks: Application to speech
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    Chapter 7 Noise in integrate-and-fire models of neuronal dynamics
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    Chapter 8 Coarse coding accounts for improvement of spatial discrimination after plastic reorganization in rats and humans
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    Chapter 9 Analogue resolution in a model of the Schaffer collaterals
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    Chapter 10 Modeling networks with linear (VLSI) integrate-and-fire neurons
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    Chapter 11 An information-theoretic analysis of temporal coding strategies by spiking central neurons
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    Chapter 12 Correlation coding in stochastic neural networks
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    Chapter 13 Two-dimensional Hodgkin-Huxley equations for investigating a basis of pulse-processing neural networks
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    Chapter 14 Concurrent parallel-sequential processing in gamma controlled cortical-type networks of spiking neurones
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    Chapter 15 Artificial Neural Networks — ICANN'97
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    Chapter 16 A novelty detector using a network of integrate and fire neurons
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    Chapter 17 Derivation of pool dynamics from microscopic neuronal models
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    Chapter 18 How a single Purkinje cell could learn the adaptive timing of the classically conditioned eye-blink response
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    Chapter 19 An algorithm for synaptic modification based on exact timing of pre- and post-synaptic action potentials
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    Chapter 20 Modelling plasticity in rat barrel cortex induced by one spared whisker
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    Chapter 21 Mathematical analysis of competition between sensory ganglion cells for nerve growth factor in the skin
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    Chapter 22 Competition amongst neurons for neurotrophins
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    Chapter 23 Implementing hebbian learning in a rank-based neural network
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    Chapter 24 Artificial Neural Networks — ICANN'97
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    Chapter 25 Hebbian delay adaptation in a network of integrate-and-fire neurons
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    Chapter 26 Hippocampal formation trains independent components via forcing input reconstruction
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    Chapter 27 Nature vs. nurture in the development of tangential connections and functional maps in the visual cortex
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    Chapter 28 Geometric relationships between feature maps in cat visual cortex
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    Chapter 29 A linear hebbian model for the development of spatiotemporal receptive fields of simple cells
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    Chapter 30 Synapse clustering can drive simultaneous ON-OFF and ocular-dominance segregation in a model of area 17
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    Chapter 31 Must pinwheels move during visual development ?
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    Chapter 32 Extending the TRN model in a biologically plausible way
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    Chapter 33 SOM-Model for the development of oriented receptive fields and orientation maps from non-oriented ON-center OFF-center inputs
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    Chapter 34 On the anatomical basis of field size, contrast sensitivity, and orientation selectivity in macaque striate cortex: A model study
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    Chapter 35 Statistics of natural and urban images
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    Chapter 36 A CBL network model with intracortical plasticity and natural image stimuli
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    Chapter 37 Geometry of orientation preference map determines nonclassical receptive field properties
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    Chapter 38 A model for orientation tuning and contextual effects of orientation selective receptive fields
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    Chapter 39 Objective functions for neural map formation
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    Chapter 40 Relative time scales in the self-organization of pattern classification: From “one-shot” to statistical learning
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    Chapter 41 Realization of geometric illusions and geometry of visual space with neural networks
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    Chapter 42 The Support Vector method
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    Chapter 43 On the significance of Markov decision processes
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    Chapter 44 Economical reinforcement learning for non stationary problems
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    Chapter 45 A double gradient algorithm to optimize regularization
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    Chapter 46 Global least-squares vs. EM training for the Gaussian mixture of experts
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    Chapter 47 Accelerated learning in Boltzmann Machines using mean field theory
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    Chapter 48 Adaptive online learning for nonstationary problems
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    Chapter 49 Weight discretization due to optical constraints and its influence on the generalization abilities of a simple perceptron
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    Chapter 50 Wavelet frames based estimator
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    Chapter 51 A spatio-temporal perceptron for on-line handwritten character recognition
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    Chapter 52 Learning oscillations using adaptive control
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    Chapter 53 Creation of neural networks based on developmental and evolutionary principles
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    Chapter 54 A boosting algorithm for regression
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    Chapter 55 Combining regularized neural networks
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    Chapter 56 Making stochastic networks deterministic
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    Chapter 57 Unsupervised learning in networks of spiking neurons using temporal coding
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    Chapter 58 Experiments on regularizing MLP models with background knowledge
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    Chapter 59 Elliptical basis function networks for classification tasks
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    Chapter 60 Probabilistic Neural Networks with rotated kernel functions
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    Chapter 61 Statistical control of RBF-like networks for classification
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    Chapter 62 Improving RBF networks by the feature selection approach EUBAFES
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    Chapter 63 Polynomial classifiers and support vector machines
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    Chapter 64 Unique representations of dynamical systems produced by recurrent neural networks
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    Chapter 65 Generalization of Elman networks
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    Chapter 66 Designing neural networks by a combination of structural learning and genetic algorithms
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    Chapter 67 A recurrent self-organizing map for temporal sequence processing
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    Chapter 68 An extended Elman net for modeling time series
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    Chapter 69 Recurrent associative memory network of nonlinear coupled oscillators
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    Chapter 70 A layered recurrent neural network for feature grouping
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    Chapter 71 A multilayer real-time, recurrent learning algorithm for improved convergence
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    Chapter 73 A novel associative network accommodating pattern deformation
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    Chapter 74 Adaptive noise injection for input variables relevance determination
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    Chapter 75 Input selection with partial retraining
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    Chapter 76 On the complexity of recognizing iterated differences of polyhedra
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    Chapter 77 Optimal linear regression on classifier outputs
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    Chapter 78 Learning verification in multilayer neural networks
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    Chapter 79 Design of a fault tolerant multilayer perceptron with a desired level of robustness
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    Chapter 80 Mixtures of experts estimate a posteriori probabilities
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    Chapter 81 Admissibility and optimality of the cascade-correlation algorithm
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    Chapter 82 The effective VC dimension of the n-tuple classifier
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    Chapter 83 From neural principal components to neural independent components
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    Chapter 84 Entropy optimization
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    Chapter 85 Improving the performance of infomax using statistical signal processing techniques
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    Chapter 86 A maximum likelihood approach to nonlinear blind source separation
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    Chapter 87 A perceptron-based approach to piecewise linear modeling with an application to time series
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    Chapter 88 Local independent component analysis by the self-organizing map
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    Chapter 89 Model breaking detection using independent component classifier
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    Chapter 90 Neural network based processing for smart sensors arrays
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    Chapter 91 Application of the MEC network to principal component analysis and source separation
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    Chapter 92 Semi-blind source parameter separation
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    Chapter 93 Kernel principal component analysis
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    Chapter 94 An empirical comparison of dimensionality reduction techniques for pattern classification
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    Chapter 95 Topology representing networks for intrinsic dimensionality estimation
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    Chapter 96 SOM based visualization in data analysis
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    Chapter 97 ARTMAP-DS: pattern discrimination by discounting similarities
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    Chapter 98 A self-organizing network that can follow non-stationary distributions
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    Chapter 99 Phase transitions in soft topographic vector quantization
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    Chapter 100 Vector quantization by optimal neural gas
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    Chapter 101 Convergences of the Kohonen maps: a dynamical system approach
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    Chapter 102 Local Subspace Classifier
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    Chapter 103 Asymptotic distributions associated to unsupervised Oja's learning equation
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    Chapter 104 The probabilistic growing cell structures algorithm
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    Chapter 105 Unsupervised coding with lococode
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    Chapter 106 Wave propagation in self-organizing feature maps as a means for the representation of temporal sequences
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    Chapter 107 Contextual kohonen SOM with orthogonal weight estimator principle
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    Chapter 108 Self-organizing maps for robot control
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    Chapter 109 Cognition is not computation; Evolution is not optimisation
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    Chapter 110 Information theoretic implications of embodiment for neural network learning
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    Chapter 111 Visual attention and learning of a cognitive robot
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    Chapter 112 Feature binding through temporally correlated neural activity in a robot model of visual perception
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    Chapter 113 Modeling obstacle avoidance behavior of flies using an adaptive autonomous agent
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    Chapter 114 Minimalistic approach to 3D obstacle avoidance behavior from simulated evolution
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    Chapter 115 Synthesis of developmental and evolutionary modeling of adaptive autonomous agents
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    Chapter 116 Hebbian multilayer network in a wheelchair robot
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    Chapter 117 Neural networks in an artificial life perspective
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    Chapter 118 Incremental acquisition of local networks for the control of autonomous robots
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    Chapter 119 Robot-animal interaction
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    Chapter 120 The view-graph approach to visual navigation and spatial memory
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    Chapter 121 Place sequence learning for navigation
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    Chapter 122 Learning to communicate through imitation in autonomous robots
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    Chapter 123 On learning soccer strategies
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    Chapter 124 A model of logic like inference by memory model PATON
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    Chapter 125 Force feedback control of an assembly robot by neural networks
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    Chapter 126 Neural force control (NFC) for complex manipulator tasks
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    Chapter 127 A hybrid path planning system combining the A*-method and RBF-networks
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    Chapter 128 An ASSOM neural network to represent actions performed by an autonomous agent
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    Chapter 129 The application of radial basis function networks with implicit continuity constraints
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    Chapter 130 Autonomous vehicle guidance using analog VLSI neuromorphic sensors
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    Chapter 131 Neural network visual tracking system
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    Chapter 132 Pole-balancing with different evolved neurocontrollers
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    Chapter 133 Calibration of parallel robots by evolutionary algorithm
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    Chapter 134 On use of ANNs to model and to control robot manipulators
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    Chapter 135 Identification of the electric arc of a furnace
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    Chapter 136 On using MLPs for step size control in echo cancellation for hands-free telephone sets
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    Chapter 137 Neurocontrol of nonlinear dynamic systems subject to unmeasured disturbance inputs
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    Chapter 138 Multiple multivariate regression and global optimization in a large scale thermodynamical application
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    Chapter 139 A neural network for parameter estimation of a DC motor for feed-drives
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    Chapter 140 State-of-the-art and recent progress in hybrid HMM/ANN speech recognition
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    Chapter 141 Perceptual grouping and attention during cortical form and motion processing
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    Chapter 142 Development of shape primitives from images of composite objects represented by complex cells
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    Chapter 143 Corner detection in color images by multiscale combination of end-stopped cortical cells
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    Chapter 144 Constructing the cyclopean view
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    Chapter 145 SAIM: A model of visual attention and neglect
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    Chapter 146 Object selection with dynamic neural maps
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    Chapter 147 A pre-processing technique based on the wavelet transform for linear autoassociators with applications to face recognition
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    Chapter 148 Recognition and segmentation of components of a face by a multi-resolution neural network
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    Chapter 149 Sensor fusion for mine detection with the RNN
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    Chapter 150 Image segmentation for 3D object recognition using bidirectional networks
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    Chapter 151 A feature map approach to pose estimation based on quaternions
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    Chapter 152 Facial feature detection using neural networks
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    Chapter 154 AdaBoosting neural networks: Application to on-line character recognition
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    Chapter 155 Cursive script recognition with time delay neural networks using learning hints
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    Chapter 156 A powerful tool for fitting and forecasting deterministic and stochastic processes: The Kohonen classification
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    Chapter 157 Neural model selection: How to determine the fittest criterion?
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    Chapter 158 Long term forecasting by combining Kohonen algorithm and standard prevision
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    Chapter 159 Predicting time series with support vector machines
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    Chapter 160 An extended neuron model for efficient timeseries generation and prediction
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    Chapter 161 Different model types for short-term forecasting of characteristic load points
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    Chapter 162 Assessing error bars in distribution load curve estimation
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    Chapter 163 Building high performant classifiers by Integrating bayesian learning, mutual Information and committee techniques — A case study in time series prediction —
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    Chapter 164 A probability estimation based criteria for model evaluation
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    Chapter 165 Short-term load forecasting based on correlation dimension estimation and neural nets
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    Chapter 166 Predictive neural models in noisy environment
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    Chapter 167 A Neural—FIR predictor: Minimum size estimation based on nonlinearity analysis of input sequence
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    Chapter 168 Modelling conditional probabilities with committees of RVFL networks
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    Chapter 169 Classifying the wear of turning tools with neural networks
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    Chapter 170 Detection of mobile phone fraud using supervised neural networks: A first prototype
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    Chapter 171 Wiener type SOM-and MLP-Classifiers for recognition of dynamic modes
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    Chapter 172 Analysis of wake/sleep EEG with competing experts
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    Chapter 173 Nonlinear modelling of the daily heart rhythm
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    Chapter 174 Linear and nonlinear combinations of connectionist models for local diagnosis in real-time telephone network traffic management
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    Chapter 175 Neural network adaptive modeling of battery discharge behavior
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    Chapter 176 Neural combustion control
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    Chapter 177 A neural network based fault detector for power distribution systems
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    Chapter 178 Visualization and analysis of voltage stability using self-organizing neural networks
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    Chapter 179 Classification of meteorological patterns
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    Chapter 180 Mapping of soil contamination by using artificial neural networks and multivariate geostatistics
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    Chapter 181 Pseudo-resistive networks and their applications to analog collective computation
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    Chapter 182 Implementation of CNN computing technology
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    Chapter 183 Implementation of a masking network for speech perception
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    Chapter 184 Real-time analog VLSI sensors for 2-D direction of motion
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    Chapter 185 An improved multiplexed resistive network for analog image preprocessing
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    Chapter 186 An analog VLSI computational engine for early vision tasks
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    Chapter 187 Spatio-temporal filter adjustment from evaluative feedback for a retina implant
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    Chapter 188 Simulation of spiking neural networks on different hardware platforms
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    Chapter 189 Adaptive on-line learning algorithm for robust estimation of parameters of noisy sinusoidal signals
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    Chapter 190 Analog sequential architecture for neuro-fuzzy models VLSI implementation
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    Chapter 191 A mixed-signal VLSI circuit for skeletonization by grassfire transformation
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    Chapter 192 Analysis and improvement of neural network robustness for on-board satellite image processing
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    Chapter 193 On-line Hebbian learning for spiking neurons: Architecture of the weight-unit of NESPINN
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    Chapter 194 Measurement of finite-precision effects in handwriting- and speech-recognition algorithms
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    Chapter 195 A hardware implementation of hierarchical Neural Networks for real-time quality control systems in industrial applications
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    Chapter 196 The SAND neurochip and its embedding in the MiND system
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    Chapter 197 Short- and long-term dynamics in a stochastic pulse stream neuron implemented in FPGA
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    Chapter 198 FPGA implementation of a network of neuronlike adaptive elements
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    Chapter 199 Handwritten digit recognition with binary optical perceptron
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    Chapter 200 Mapping of radial basis function networks to partial tree shape parallel neurocomputer
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    Chapter 201 Attractor dynamics in an electronic neural network
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Title
Artificial Neural Networks — ICANN'97 : 7th International Conference Lausanne, Switzerland, October 8–10, 1997 Proceeedings
Published by
Springer, Berlin, Heidelberg, January 1997
DOI 10.1007/bfb0020124
ISBNs
978-3-54-063631-1, 978-3-54-069620-9
Editors

Gerstner, Wulfram, Nicoud, Jean-Daniel, Hasler, Martin, Germond, Alain

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The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 8%
Germany 1 3%
United States 1 3%
Unknown 34 87%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 26%
Researcher 8 21%
Student > Ph. D. Student 7 18%
Student > Bachelor 5 13%
Unspecified 4 10%
Other 5 13%
Readers by discipline Count As %
Computer Science 15 38%
Engineering 9 23%
Mathematics 4 10%
Unspecified 4 10%
Business, Management and Accounting 3 8%
Other 4 10%