Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003

Learning Algorithms.- Adaptive Hopfield Network.- Effective Pruning Method for a Multiple Classifier System Based on Self-Generating Neural Networks.- Structural Bias in Inducing Representations for Probabilistic Natural Language Parsing.- Independent Component Analysis Minimizing Convex Divergence.- Selecting Salient Features for Classification Committees.- Fast and Efficient Training of RBF Networks.- Loading Temporal Associative Memory Using the Neuronic Equation.- Learning Compatibility Functions for Feature Binding and Perceptual Grouping.- Differential ICA.- A Comparison of Model Aggregation Methods for Regression.- Linear Least-Squares Based Methods for Neural Networks Learning.- Optimal Hebbian Learning: A Probabilistic Point of View.- Competitive Learning by Information Maximization: Eliminating Dead Neurons in Competitive Learning.- Approximate Learning in Temporal Hidden Hopfield Models.- Finite Mixture Model of Bounded Semi-naive Bayesian Networks Classifier.- System Identification Based on Online Variational Bayes Method and Its Application to Reinforcement Learning.- Dimension Reduction Based on Orthogonality — A Decorrelation Method in ICA.- Selective Sampling Methods in One-Class Classification Problems.- Learning Distributed Representations of High-Arity Relational Data with Non-linear Relational Embedding.- Meta-learning for Fast Incremental Learning.- Expectation-MiniMax Approach to Clustering Analysis.- Formal Determination of Context in Contextual Recursive Cascade Correlation Networks.- Confidence Estimation Using the Incremental Learning Algorithm, Learn++.- Stability and Convergence Analysis of a Neural Model Applied in Nonlinear Systems Optimization.- SVM and Kernel Methods.- Generalization Error Analysis for Polynomial Kernel Methods — Algebraic Geometrical Approach.- Regularized Kriging: The Support Vectors Method Applied to Kriging.- Support Vector Machine Classifiers for Asymmetric Proximities.- Fuzzy Model Identification Using Support Vector Clustering Method.- Human Splice Site Identification with Multiclass Support Vector Machines and Bagging.- Statistical Data Analysis.- Optimizing Property Codes in Protein Data Reveals Structural Characteristics.- Multicategory Bayesian Decision Using a Three-Layer Neural Network.- Integrating Supervised and Unsupervised Learning in Self Organizing Maps for Gene Expression Data Analysis.- Prior Hyperparameters in Bayesian PCA.- Relevance and Kernel Self-Organising Maps.- Pattern Recognition.- Hierarchical Bayesian Network for Handwritten Digit Recognition.- A Novel Neural Network Approach to Solve Exact and Inexact Graph Isomorphism Problems.- Evolutionary Optimisation of RBF Network Architectures in a Direct Marketing Application.- Intrusion Detection in Computer Networks with Neural and Fuzzy Classifiers.- Optimal Matrix Compression Yields Storage Capacity 1 for Binary Willshaw Associative Memory.- Supervised Locally Linear Embedding.- Feature Extraction for One-Class Classification.- Auto-adaptive and Dynamical Clustering Neural Network.- Transformations of Symbolic Data for Continuous Data Oriented Models.- Comparing Fuzzy Data Sets by Means of Graph Matching Technique.- How to Do Multi-way Classification with Two-Way Classifiers.- Vision.- Sparse Coding with Invariance Constraints.- Restoring Partly Occluded Patterns: A Neural Network Model with Backward Paths.- The InfoMin Criterion: An Information Theoretic Unifying Objective Function for Topographic Mappings.- Short-Term Memory Optical Flow Image.- A Hybrid MLP-PNN Architecture for Fast Image Superresolution.- Recognition of Gestural Object Reference with Auditory Feedback.- Multi-chip Implementation of a Biomimetic VLSI Vision Sensor Based on the Adelson-Bergen Algorithm.- Speech Recognition.- Client Dependent GMM-SVM Models for Speaker Verification.- Frequency and Wavelet Filtering for Robust Speech Recognition.- Robotics and Control.- Unsupervised Learning of a Kinematic Arm Model.- A Design of CMAC Based Intelligent PID Controllers.- Learning to Control at Multiple Time Scales.- The Evolution of Modular Artificial Neural Networks for Legged Robot Control.- Dimensionality Reduction through Sensory-Motor Coordination.- Learning Localisation Based on Landmarks Using Self-Organisation.- Signal Processing.- Spatial Independent Component Analysis of Multitask-Related Activation in fMRI Data.- Closed Loop Stability of FIR-Recurrent Neural Networks.- Selective Noise Cancellation Using Independent Component Analysis.- Expert Mixture Methods for Adaptive Channel Equalization.- A Relaxation Algorithm Influenced by Self-Organizing Maps.- A Gradient Network for Vector Quantization and Its Image Compression Applications.- Multi-scale Switching Linear Dynamical Systems.- Time-Series Prediction.- Model Selection with Cross-Validations and Bootstraps — Application to Time Series Prediction with RBFN Models.- A Hybrid Neural Architecture and Its Application to Temperature Prediction.- Risk Management Application of the Recurrent Mixture Density Network Models.- Hierarchical Mixtures of Autoregressive Models for Time-Series Modeling.- Intelligent and Hybrid Systems.- A Simple Constructing Approach to Build P2P Global Computing Overlay Network.- Option Pricing with the Product Constrained Hybrid Neural Network.- Self-Organizing Operator Maps in Complex System Analysis.- Optimization of a Microwave Amplifier Using Neural Performance Data Sheets with Genetic Algorithms.- Adaptive Stochastic Classifier for Noisy pH-ISFET Measurements.- Comparing Support Vector Machines, Recurrent Networks, and Finite State Transducers for Classifying Spoken Utterances.- Selecting and Ranking Time Series Models Using the NOEMON Approach.- Optimization of the Deflection Basin by Genetic Algorithm and Neural Network Approach.- Inversion of a Neural Network via Interval Arithmetic for Rule Extraction.- Implementation of Visual Attention System Using Bottom-up Saliency Map Model.- A Self-Growing Probabilistic Decision-Based Neural Network for Anchor/Speaker Identification.- Unsupervised Clustering Methods for Medical Data: An Application to Thyroid Gland Data.- Protein Sequence Classification Using Probabilistic Motifs and Neural Networks.- On a Dynamic Wavelet Network and Its Modeling Application.- Neural Network Hardware.- Low Power Digital Neuron for SOM Implementations.- Direction Selective Two-Dimensional Analog Circuits Using Biomedical Vision Model.- Review of Capacitive Threshold Gate Implementations.- Constructive Threshold Logic Addition.- CrossNets: Neuromorphic Networks for Nanoelectronic Implementation.- Cognitive Science.- The Acquisition of New Categories through Grounded Symbols: An Extended Connectionist Model.- A Neural Model of Binding and Capacity in Visual Working Memory.- Neural Network: Input Anticipation May Lead to Advanced Adaptation Properties.- Acceleration of Game Learning with Prediction-Based Reinforcement Learning — Toward the Emergence of Planning Behavior —.- Computational Neuroscience.- The Interaction of Recurrent Axon Collateral Networks in the Basal Ganglia.- Optimal Coding for Naturally Occurring Whisker Deflections.- Object Localisation Using Laterally Connected “What” and “Where” Associator Networks.- Influence of Membrane Warp on Pulse Propagation Time.- Detailed Learning in Narrow Fields – Towards a Neural Network Model of Autism.- Online Processing of Multiple Inputs in a Sparsely-Connected Recurrent Neural Network.- The Spike Response Model: A Framework to Predict Neuronal Spike Trains.- Roles of Motion and Form in Biological Motion Recognition.- Special Sessions.- Improving the Performance of Resource Allocation Networks through Hierarchical Clustering of High-Dimensional Data.- Learning Rule Representations from Boolean Data.- Weighted Self-Organizing Maps: Incorporating User Feedback.- Classification and Tracking of Hypermedia Navigation Patterns.- Self-Aware Networks and Quality of Service.- Drawing Attention to the Dangerous.- ASK – Acquisition of Semantic Knowledge.- An Adaptable Gaussian Neuro-Fuzzy Classifier.- Knowledge Refinement Using Fuzzy Compositional Neural Networks.- Complex-Valued Neural Networks: Theories and Applications.- Phase Singular Points Reduction by a Layered Complex-Valued Neural Network in Combination with Constructive Fourier Synthesis.- Quantum Adiabatic Evolution Algorithm for a Quantum Neural Network.- Adaptive Beamforming by Using Complex-Valued Multi Layer Perceptron.- A Complex-Valued Spiking Machine.- The behavior of the network consisting of two complex-valued Nagumo-Sato neurons.- On Activation Functions for Complex-Valued Neural Networks — Existence of Energy Functions —.- The Computational Power of Complex-Valued Neuron.- Computational Intelligence and Applications.- Recommendation Models for User Accesses to Web Pages.- A Spectral–Spatial Classification Algorithm for Multispectral Remote Sensing Data.- Neural Network Based Material Identification and Part Thickness Estimation from Two Radiographic Images.- Selection of Optimal Cutting Conditions by Using the Genetically Optimized Neural Network System (GONNS).- Building RBF Neural Network Topology through Potential Functions.- Use of Magnetomyographic (MMG) Signals to Calculate the Dependency Properties of the Active Sensors in Myometrial Activity Monitoring.- Speed Enhancement with Soft Computing Hardware.- Neural Networks Applied to Electromagnetic Compatibility (EMC) Simulations.- Sliding Mode Algorithm for Online Learning in Analog Multilayer Feedforward Neural Networks.- Exploring Protein Functional Relationships Using Genomic Information and Data Mining Techniques.- Predicting Bad Credit Risk: An Evolutionary Approach.- Indirect Differentiation of Function for a Network of Biologically Plausible Neurons.- Application of Vision Models to Traffic Sign Recognition.- Emotional Recognition.- An Intelligent Scheme for Facial Expression Recognition.- Signal Enhancement for Continuous Speech Recognition.- Emotion in Speech: Towards an Integration of Linguistic, Paralinguistic, and Psychological Analysis.- An Emotional Recognition Architecture Based on Human Brain Structure.- Neural Networks for Bio-informatics Applications.- Neural Network Ensemble with Negatively Correlated Features for Cancer Classification.- Feature Analysis and Classification of Protein Secondary Structure Data.- Recognition of Structure Classification of Protein Folding by NN and SVM Hierarchical Learning Architecture.- Machine Learning for Multi-class Protein Fold Classification Based on Neural Networks with Feature Gating.- Some New Features for Protein Fold Prediction.