2003, XLIV, 1194 p. In 2 volumes, not available separately.
Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
This book constitutes the refereed proceedings of the joint International Conference on Artificial Neural Networks and International Conference on Neural Information Processing, ICANN/ICONIP 2003, held in Istanbul, Turkey, in June 2003.
The 138 revised full papers were carefully reviewed and selected from 346 submissions. The papers are organized in topical sections on learning algorithms, support vector machine and kernel methods, statistical data analysis, pattern recognition, vision, speech recognition, robotics and control, signal processing, time-series prediction, intelligent systems, neural network hardware, cognitive science, computational neuroscience, context aware systems, complex-valued neural networks, emotion recognition, and applications in bioinformatics.
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.