Artificial Neural Networks - ICANN 96: 6th International Conference, Bochum, Germany, July 16 - 19, 1996. ProceedingsChristoph von der Malsburg Springer Science & Business Media, 1996. gada 10. jūl. - 922 lappuses This book constitutes the refereed proceedings of the sixth International Conference on Artificial Neural Networks - ICANN 96, held in Bochum, Germany in July 1996. The 145 papers included were carefully selected from numerous submissions on the basis of at least three reviews; also included are abstracts of the six invited plenary talks. All in all, the set of papers presented reflects the state of the art in the field of ANNs. Among the topics and areas covered are a broad spectrum of theoretical aspects, applications in various fields, sensory processing, cognitive science and AI, implementations, and neurobiology. |
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Saturs
Application of Artificial Neural Networks in Particle Physics | 1 |
Evolutionary Computation History Status and Perspectives | 15 |
Temporal Structure of Cortical Activity | 16 |
SEE1 A Vision System for Use in Real World Environments | 17 |
Towards Integration of Nerve Cells and Silicon Devices | 18 |
Unifying Perspectives on Neuronal Codes and Processing | 19 |
Analysis of Pattern Configuration and Generalisation across Viewing Conditions without Mental Rotation | 20 |
A Novel Encoding Strategy for Associative Memory | 21 |
Temporal Compositional Processing by a DSOM Hierarchical Model | 457 |
A Genetic Model and the Hopfield Networks | 463 |
Desaturating Coefficient for Projection Learning Rule | 469 |
Getting More Information out of SDM | 477 |
Using a General Purpose Meta Neural Network to Adapt a Parameter of the Quickpropagation Learning Rule | 483 |
Unsupervised Learning of the Minor Subspace | 489 |
The GANNFL Approach | 495 |
Active Learning of the Generalized HighLowGame | 501 |
Autoassociative Memory with high Storage Capacity | 29 |
Information Efficiency of the Associative Net at Arbitrary Coding Rates | 35 |
Efficient Learning in Sparsely Connected Boltzmann Machines | 41 |
Incorporating Invariances in Support Vector Learning Machines | 47 |
Estimating the Reliability of Neural Network Classifications | 53 |
Bayesian Inference of Noise Levels in Regression | 59 |
Complexity Reduction in Probabilistic Neural Networks | 65 |
Asymptotic Complexity of an RBF NN for Correlated Data Representation | 71 |
Regularization by Early Stopping in Single Layer Perceptron Training | 77 |
Clustering in Weight Space of Feedforward Nets | 83 |
Learning Curves of Online and Offline Training | 89 |
Learning Structure with ManyTakeAll Networks | 95 |
Dynamic Feature Linking in Stochastic Networks with Short Range Interactions | 101 |
Collective Dynamics of a System of Adaptive Velocity Channels | 107 |
Local Linear Model Trees for OnLine Identification of TimeVariant Nonlinear Dynamic Systems | 115 |
A CumulantSurrogate Method | 121 |
Prediction of Mixtures | 127 |
Learning Dynamical Systems Produced by Recurrent Neural Networks | 133 |
Purely Local Neural Principal Component and Independent Component Learning | 139 |
How Fast Can Neuronal Algorithms Match Patterns? | 145 |
An Annealed Neural Gas Network for Robust Vector Quantization | 151 |
Associative Completion and Investment Learning Using PSOMs | 157 |
A Principled Alternative to the SelfOrganizing Map | 165 |
Creating Term Associations Using a Hierarchical ART Architecture | 171 |
Architecture Selection Through Statistical Sensitivity Analysis | 179 |
Application on Real Data | 185 |
Signal Processing by Neural Networks to Create Virtual Sensors and ModelBased Diagnostics | 191 |
Development of an Advisory System Based on a Neural Network for the Operation of a Coal Fired Power Plant | 197 |
Blast Furnace Analysis with Neural Networks | 203 |
Diagnosis Tools for Telecommunication Network Traffic Management | 209 |
Adaptive Saccade Control of a Binocular Head with Dynamic Cell Structures | 215 |
Learning Fine Motion by Using the Hierarchical Extended Kohonen Map | 221 |
Subspace Dimension Selection and Averaged Learning Subspace Method in Handwritten Digit Classification | 227 |
A Dual Route Neural Net Approach to GraphemetoPhoneme Conversion | 233 |
Separating EEG SpikeClusters in Epilepsy by a Growing and Splitting Net | 239 |
Optimal Texture Feature Selection for the Cooccurrence Map | 245 |
Comparison of ViewBased Object Recognition Algorithms Using Realistic 3D Models | 251 |
ColorCalibration of a Robot Vision System Using SelfOrganizing Feature Maps | 257 |
Neural Network Model for Maximum Ozone Concentration Prediction | 263 |
Very Large TwoLevel SOM for the Browsing of Newsgroups | 269 |
Automatic PartOfSpeech Tagging of Thai Corpus Using Neural Networks | 275 |
Reproducing a Subjective Classification Scheme for Atmospheric Circulation Patterns over the United Kingdom using a Neural Network | 281 |
Two Gradient Descent Algorithms for Blind Signal Separation | 287 |
Classification Rejection by Prediction | 293 |
Application of Radial Basis Function Neural Networks to Odour Sensing Using a Broad Specificity Array of Conducting Polymers | 299 |
A Hybrid Object Recognition Architecture | 305 |
Robot Learning in Analog Neural Hardware | 311 |
Visual Gesture Recognition by a Modular Neural System | 317 |
Tracking and Learning Graphs on Image Sequences of Faces | 323 |
Neural Network Model Recalling Spatial Maps | 329 |
Neural Field Dynamics for Motion Perception | 335 |
Analytical Technique for Deriving Connectionist Representations of Symbol Structures | 341 |
Modeling Human Word Recognition with Sequences of Artificial Neurons | 347 |
A Connectionist Variation on Inheritance | 353 |
Mapping of Multilayer Perceptron Networks to Partial Tree Shape Parallel Neurocomputer | 359 |
Linearly Expandable Partial Tree Shape Architecture for Parallel Neurocomputer | 365 |
A HighSpeed Scalable CMOS CurrentMode WinnerTakeAll Network | 371 |
An Architectural Study of a Massively Parallel Processor for ConvolutionType Operations in Complex Vision Tasks | 377 |
FPGA Implementation of an Adapt ableSize Neural Network | 383 |
Extraction of Coherent Information from NonOverlapping Receptive Fields | 389 |
CorticoTectal Interactions in the Cat Visual System | 395 |
A Bayesian Approach | 401 |
Analyzing the Formation of Structure in HighDimensional SelfOrganizing Maps Reveals Differences to Feature Map Models | 409 |
Maps Explained by Hebbian Dynamics of Geniculocortical Connections | 415 |
Modification of Kohonens SOFM to Simulate Cortical Plasticity Induced by Coactivation Input Patterns | 421 |
Cortical Map Development Driven by Spontaneous Retinal Activity Waves | 427 |
Simplifying neural networks for controlling walking by exploiting physical properties | 433 |
TwoDimensional Neural Field Model | 439 |
Plasticity of Neocortical Synapses Enables Transitions Between Rate and Temporal Coding | 445 |
Controlling the Speed of Synfire Chains | 451 |
Optimality of Pocket Algorithm | 507 |
Improvements and Extensions to the Constructive Algorithm CARVE | 513 |
Annealed RNN Learning of Finite State Automata | 519 |
A Hierarchical Learning Rule for Independent Component Analysis | 525 |
Improving Neural Network Training Based on Jacobian Rank Deficiency | 531 |
Neural Networks for Exact Constrained Optimization | 537 |
Capacity of Structured Multilayer Networks with Shared Weights | 543 |
Optimal Weight Decay in a Perceptron | 551 |
Bayesian Regularization in Constructive Neural Networks | 557 |
A Nonlinear Discriminant Algorithm for Data Projection and Feature Extraction | 563 |
A Modified Spreading Algorithm for Autoassociation in Weightless Neural Networks | 569 |
Analysis of MultiFluorescence Signals Using a Modified SelfOrganizing Feature Map | 575 |
Visualizing Similarities in High Dimensional Input Spaces with a Growing and Splitting Neural Network | 581 |
A Neural Lexical PostProcessor for Improved Neural Predictive Word Recognition | 587 |
A Comparative Study Using Neural Networks | 593 |
Combining Statistical Models for Protein Secondary Structure Prediction | 599 |
Using RBFNets in Rubber Industry Process Control | 605 |
Towards Autonomous Robot Control via SelfAdapting Recurrent Networks | 611 |
A Hierarchical Network for Learning Robust Models of Kinematic Chains | 617 |
ContextBased Cognitive Map Learning for an Autonomous Robot Using a Model of CorticoHippocampal Interplay | 623 |
An Algorithm for Bootstrapping the Core of a Biologically Inspired Motor Control System | 629 |
An Industrial Prototype | 635 |
Population Coding in Cat Visual Cortex Reveals Nonlinear Interactions as Predicted by a Neural Field Model | 641 |
Representing Multidimensional Stimuli on the Cortex | 649 |
An Analysis and Interpretation of the Oscillatory Behaviour of a Model of the Granular Layer of the Cerebellum | 655 |
The Cerebellum as a Coupling Machine | 661 |
A Computational Model | 667 |
Signatures of Dynamic Cell Assemblies in Monkey Motor Cortex | 673 |
Modelling Speech Processing and Recognition in the Auditory System with a ThreeStage Architecture | 679 |
BindingA Proposed Experiment and a Model | 685 |
A Reduced Model for Dendritic Trees with Active Membrane | 691 |
Stabilizing Competitive Learning during Online Training with an AntiHebbian Weight Modulation | 697 |
Neurobiological Bases for Spatiotemporal Data Coding in Artificial Neural Networks | 703 |
A SpatioTemporal Learning Rule Based on the Physiological Data of LTP Induction in the Hippocampal CA1 Network | 709 |
Learning Novel Views to a Single Face Image | 715 |
A Parallel Algorithm for Depth Perception from Radial Optical Flow Fields | 721 |
A Case Study on PHANTOMAS | 727 |
Geometrically Constrained Optical Flow Estimation by an Hopfield Neural Network | 735 |
Serial Binary Addition with Polynomially Bounded Weights | 741 |
Evaluation of the Two Different Interconnection Networks of the CNAPS Neurocomputer | 747 |
Intrinsic and Parallel Performances of the OWE Neural Network Architecture | 755 |
Multilevel Weight Storage | 761 |
Exponential Hebbian OnLine Learning Implemented in FPGAs | 767 |
An InformationTheoretic Measure for the Classification of Time Series | 773 |
Transformation of Neural Oscillators | 779 |
Analysis of Drifting Dynamics with Competing Predictors | 785 |
Consequences for Neurocontrollers | 791 |
A Local Connected Neural Oscillator Network for Pattern Segmentation | 797 |
Approximation Errors of State and Output Trajectories Using Recurrent Neural Networks | 803 |
Comparing SelfOrganizing Maps | 809 |
Nonlinear Independent Component Analysis by SelfOrganizing Maps | 815 |
Building Nonlinear Data Models with SelfOrganizing Maps | 821 |
A ParameterFree NonGrowing SelfOrganizing Map Based upon Gravitational Principles Algorithm and Applications | 827 |
Topological Maps for Mixture Densities | 833 |
A Novel Algorithm for Image Segmentation Using Time Dependent Interaction Probabilities | 839 |
Reconstruction from graphs labeled with responses of Gabor filters | 845 |
A Confidence Based Algorithm Emphazising Continuous Curves | 851 |
Neural Model of Cortical Dynamics in Resonant Boundary Detection and Grouping | 857 |
A Neural Clustering Algorithm for Estimating Visible Articulatory Trajectory | 863 |
Binary SpatterCoding of Ordered Atuples | 869 |
A Hybrid Approach to Natural Language Parsing | 875 |
A SelfOrganizing Neural Network Approach for the Acquisition of Phonetic Categories | 881 |
A Step Towards LongTerm Memory | 887 |
Neural Modelling of Cognitive Disinhibition and Neurotransmitter Dysfunction in OCD | 893 |
Confluent Preorder Parser As Finite State Automata | 899 |
Modeling Psychological Stereotypes in SelfOrganizing Maps | 905 |
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Bieži izmantoti vārdi un frāzes
activity adaptation analysis applications approach approximation architecture Artificial Neural Networks backpropagation Boltzmann Machine cells cerebellum classification clusters coding complex components computed connectionist connections convergence correlation corresponding cortex cortical defined denote distance distribution dynamics encoding equation error estimation example feature feedback feedforward Figure FPGA function Gabor filters Gaussian given Hamming distance Hebbian learning hidden layer hidden units IEEE implementation input space input vector interaction iterations Kohonen learning algorithm learning rule linear matrix memory method neural oscillator neurons nodes nonlinear object obtained optimal orientation oscillator parameters patterns perceptron performance phase pixels prediction problem proposed receptive fields recognition recurrent neural network representation represents robot sample segmentation Self-Organizing Maps sensor sequence shows signal simulation spatial spike statistical stimulus structure synaptic task temporal threshold tion training set transformation unsupervised learning values variables vector quantization visual weight vector