Artificial neural networks -- ICANN 2006 : 16th International Conference, Athens, Greece, September 10-14, 2006 : proceedings
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書誌事項
Artificial neural networks -- ICANN 2006 : 16th International Conference, Athens, Greece, September 10-14, 2006 : proceedings
（Lecture notes in computer science, 4131,
Springer, c2006
- Part 1
- Part 2
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注記
Includes bibliographical references and index
Other editors: Andreas Stafylopatis, Włodzisław Duch, Erkki Oja
内容説明・目次
- 巻冊次
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Part 1 ISBN 9783540386254
内容説明
The two-volume set LNCS 4131 and LNCS 4132 constitutes the refereed proceedings of the 16th International Conference on Artificial Neural Networks, ICANN 2006. The set presents 208 revised full papers, carefully reviewed and selected from 475 submissions. This first volume presents 103 papers, organized in topical sections on feature selection and dimension reduction for regression, learning algorithms, advances in neural network learning methods, ensemble learning, hybrid architectures, and more.
目次
Feature Selection and Dimension Reduction for Regression (Special Session).- Dimensionality Reduction Based on ICA for Regression Problems.- A Functional Approach to Variable Selection in Spectrometric Problems.- The Bayes-Optimal Feature Extraction Procedure for Pattern Recognition Using Genetic Algorithm.- Speeding Up the Wrapper Feature Subset Selection in Regression by Mutual Information Relevance and Redundancy Analysis.- Effective Input Variable Selection for Function Approximation.- Comparative Investigation on Dimension Reduction and Regression in Three Layer Feed-Forward Neural Network.- Learning Algorithms (I).- On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition.- Learning Long Term Dependencies with Recurrent Neural Networks.- Adaptive On-Line Neural Network Retraining for Real Life Multimodal Emotion Recognition.- Time Window Width Influence on Dynamic BPTT(h) Learning Algorithm Performances: Experimental Study.- Framework for the Interactive Learning of Artificial Neural Networks.- Analytic Equivalence of Bayes a Posteriori Distributions.- Learning Algorithms (II).- Neural Network Architecture Selection: Size Depends on Function Complexity.- Competitive Repetition-suppression (CoRe) Learning.- Real-Time Construction of Neural Networks.- MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation.- A Variational Formulation for the Multilayer Perceptron.- Advances in Neural Network Learning Methods (Special Session).- Natural Conjugate Gradient Training of Multilayer Perceptrons.- Building Ensembles of Neural Networks with Class-Switching.- K-Separability.- Lazy Training of Radial Basis Neural Networks.- Investigation of Topographical Stability of the Concave and Convex Self-Organizing Map Variant.- Alternatives to Parameter Selection for Kernel Methods.- Faster Learning with Overlapping Neural Assemblies.- Improved Storage Capacity of Hebbian Learning Attractor Neural Network with Bump Formations.- Error Entropy Minimization for LSTM Training.- Ensemble Learning.- Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn?+?+? Under Different Combination Rules.- Ensemble Learning with Local Diversity.- A Machine Learning Approach to Define Weights for Linear Combination of Forecasts.- A Game-Theoretic Approach to Weighted Majority Voting for Combining SVM Classifiers.- Improving the Expert Networks of a Modular Multi-Net System for Pattern Recognition.- Learning Random Neural Networks and Stochastic Agents (Special Session).- Evaluating Users' Satisfaction in Packet Networks Using Random Neural Networks.- Random Neural Networks for the Adaptive Control of Packet Networks.- Hardware Implementation of Random Neural Networks with Reinforcement Learning.- G-Networks and the Modeling of Adversarial Agents.- Hybrid Architectures.- Development of a Neural Net-Based, Personalized Secure Communication Link.- Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees.- Active Learning with the Probabilistic RBF Classifier.- Merging Echo State and Feedforward Neural Networks for Time Series Forecasting.- Language and Cognition Integration Through Modeling Field Theory: Category Formation for Symbol Grounding.- A Methodology for Estimating the Product Life Cycle Cost Using a Hybrid GA and ANN Model.- Self Organization.- Using Self-Organizing Maps to Support Video Navigation.- Self-Organizing Neural Networks for Signal Recognition.- An Unsupervised Learning Rule for Class Discrimination in a Recurrent Neural Network.- On the Variants of the Self-Organizing Map That Are Based on Order Statistics.- On the Basis Updating Rule of Adaptive-Subspace Self-Organizing Map (ASSOM).- Composite Algorithm for Adaptive Mesh Construction Based on Self-Organizing Maps.- A Parameter in the Learning Rule of SOM That Incorporates Activation Frequency.- Nonlinear Projection Using Geodesic Distances and the Neural Gas Network.- Connectionist Cognitive Science.- Contextual Learning in the Neurosolver.- A Computational Model for the Effect of Dopamine on Action Selection During Stroop Test.- A Neural Network Model of Metaphor Understanding with Dynamic Interaction Based on a Statistical Language Analysis.- Strong Systematicity in Sentence Processing by an Echo State Network.- Modeling Working Memory and Decision Making Using Generic Neural Microcircuits.- A Virtual Machine for Neural Computers.- Cognitive Machines (Special Session).- Machine Cognition and the EC Cognitive Systems Projects: Now and in the Future.- A Complex Neural Network Model for Memory Functioning in Psychopathology.- Modelling Working Memory Through Attentional Mechanisms.- A Cognitive Model of Multi-objective Multi-concept Formation.- A Basis for Cognitive Machines.- Neural Model of Dopaminergic Control of Arm Movements in Parkinson's Disease Bradykinesia.- Occlusion, Attention and Object Representations.- A Forward / Inverse Motor Controller for Cognitive Robotics.- A Computational Model for Multiple Goals.- Neural Dynamics and Complex Systems.- Detection of a Dynamical System Attractor from Spike Train Analysis.- Recurrent Neural Networks Are Universal Approximators.- A Discrete Adaptive Stochastic Neural Model for Constrained Optimization.- Quantum Perceptron Network.- Critical Echo State Networks.- Rapid Correspondence Finding in Networks of Cortical Columns.- Adaptive Thresholds for Layered Neural Networks with Synaptic Noise.- Backbone Structure of Hairy Memory.- Dynamics of Citation Networks.- Computational Neuroscience.- Processing of Information in Synchroneously Firing Chains in Networks of Neurons.- Phase Precession and Recession with STDP and Anti-STDP.- Visual Pathways for Detection of Landmark Points.- A Model of Grid Cells Based on a Path Integration Mechanism.- Temporal Processing in a Spiking Model of the Visual System.- Accelerating Event Based Simulation for Multi-synapse Spiking Neural Networks.- A Neurocomputational Model of an Imitation Deficit Following Brain Lesion.- Temporal Data Encoding and SequenceLearning with Spiking Neural Networks.- Neural Control, Reinforcement Learning and Robotics Applications.- Optimal Tuning of Continual Online Exploration in Reinforcement Learning.- Vague Neural Network Controller and Its Applications.- Parallel Distributed Profit Sharing for PC Cluster.- Feature Extraction for Decision-Theoretic Planning in Partially Observable Environments.- Reinforcement Learning with Echo State Networks.- Reward Function and Initial Values: Better Choices for Accelerated Goal-Directed Reinforcement Learning.- Nearly Optimal Exploration-Exploitation Decision Thresholds.- Dual Adaptive ANN Controllers Based on Wiener Models for Controlling Stable Nonlinear Systems.- Online Stabilization of Chaotic Maps Via Support Vector Machines Based Generalized Predictive Control.- Robotics, Control, Planning.- Morphological Neural Networks and Vision Based Mobile Robot Navigation.- Position Control Based on Static Neural Networks of Anthropomorphic Robotic Fingers.- Learning Multiple Models of Non-linear Dynamics for Control Under Varying Contexts.- A Study on Optimal Configuration for the Mobile Manipulator: Using Weight Value and Mobility.- VSC Perspective for Neurocontroller Tuning.- A Neural Network Module with Pretuning for Search and Reproduction of Input-Output Mapping.- Bio-inspired Neural Network On-Chip Implementation and Applications (Special session).- Physical Mapping of Spiking Neural Networks Models on a Bio-inspired Scalable Architecture.- A Time Multiplexing Architecture for Inter-neuron Communications.- Neuronal Cell Death and Synaptic Pruning Driven by Spike-Timing Dependent Plasticity.- Effects of Analog-VLSI Hardware on the Performance of the LMS Algorithm.- A Portable Electronic Nose (E-Nose) System Based on PDA.- Optimal Synthesis of Boolean Functions by Threshold Functions.- Pareto-optimal Noise and Approximation Properties of RBF Networks.
- 巻冊次
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Part 2 ISBN 9783540388715
内容説明
The two-volume set LNCS 4131 and LNCS 4132 constitutes the refereed proceedings of the 16th International Conference on Artificial Neural Networks, ICANN 2006. The set presents 208 revised full papers, carefully reviewed and selected from 475 submissions. This second volume contains 105 contributions related to neural networks, semantic web technologies and multimedia analysis, bridging the semantic gap in multimedia machine learning approaches, signal and time series processing, data analysis, and more.
目次
Neural Networks, Semantic Web Technologies and Multimedia Analysis (Special Session).- The Core Method: Connectionist Model Generation.- A Neural Scheme for Robust Detection of Transparent Logos in TV Programs.- A Neural Network to Retrieve Images from Text Queries.- Techniques for Still Image Scene Classification and Object Detection.- Adaptation of Weighted Fuzzy Programs.- Classified Ranking of Semantic Content Filtered Output Using Self-organizing Neural Networks.- Classifier Fusion: Combination Methods For Semantic Indexing in Video Content.- Bridging the Semantic Gap in Multimedia Machine Learning Approaches (Special Session).- Retrieval of Multimedia Objects by Combining Semantic Information from Visual and Textual Descriptors.- A Relevance Feedback Approach for Content Based Image Retrieval Using Gaussian Mixture Models.- Video Representation and Retrieval Using Spatio-temporal Descriptors and Region Relations.- Bridging the Syntactic and the Semantic Web Search.- Content-Based Coin Retrieval Using Invariant Features and Self-organizing Maps.- Signal and Time Series Processing (I).- Learning Time-Series Similarity with a Neural Network by Combining Similarity Measures.- Prediction Improvement via Smooth Component Analysis and Neural Network Mixing.- Missing Value Estimation for DNA Microarrays with Mutliresolution Schemes.- Applying REC Analysis to Ensembles of Sigma-Point Kalman Filters.- Analysis of Fast Input Selection: Application in Time Series Prediction.- A Linguistic Approach to a Human-Consistent Summarization of Time Series Using a SOM Learned with a LVQ-Type Algorithm.- Signal and Time Series Processing (II).- Long-Term Prediction of Time Series Using State-Space Models.- Time Series Prediction Using Fuzzy Wavelet Neural Network Model.- OFDM Channel Equalization Based on Radial Basis Function Networks.- A Quasi-stochastic Gradient Algorithm for Variance-Dependent Component Analysis.- Two ICA Algorithms Applied to BSS in Non-destructive Vibratory Tests.- Reference-Based Extraction of Phase Synchronous Components.- Data Analysis (I).- Analytic Solution of Hierarchical Variational Bayes in Linear Inverse Problem.- Nonnegative Matrix Factorization for Motor Imagery EEG Classification.- Local Factor Analysis with Automatic Model Selection: A Comparative Study and Digits Recognition Application.- Interpolating Support Information Granules.- Feature Selection Based on Kernel Discriminant Analysis.- Local Selection of Model Parameters in Probability Density Function Estimation.- The Sphere-Concatenate Method for Gaussian Process Canonical Correlation Analysis.- Theory of a Probabilistic-Dependence Measure of Dissimilarity Among Multiple Clusters.- Kernel PCA as a Visualization Tools for Clusters Identifications.- Data Analysis (II).- A Fast Fixed-Point Algorithm for Two-Class Discriminative Feature Extraction.- Feature Extraction with Weighted Samples Based on Independent Component Analysis.- Discriminant Analysis by a Neural Network with Mahalanobis Distance.- Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping.- A Model Selection Method Based on Bound of Learning Coefficient.- Pattern Recognition.- Sequential Learning with LS-SVM for Large-Scale Data Sets.- A Nearest Features Classifier Using a Self-organizing Map for Memory Base Evaluation.- A Multisensor Fusion System for the Detection of Plant Viruses by Combining Artificial Neural Networks.- A Novel Connectionist-Oriented Feature Normalization Technique.- An Evolutionary Approach to Automatic Kernel Construction.- A Leave-K-Out Cross-Validation Scheme for Unsupervised Kernel Regression.- Neural Network Clustering Based on Distances Between Objects.- Rotation-Invariant Pattern Recognition: A Procedure Slightly Inspired on Olfactory System and Based on Kohonen Network.- Pattern Classification Using Composite Features.- Visual Attention Algorithms and Architectures for Perceptional Understanding and Video Coding (Special Session).- Towards a Control Theory of Attention.- Localization of Attended Multi-feature Stimuli: Tracing Back Feed-Forward Activation Using Localized Saliency Computations.- An Attention Based Similarity Measure for Colour Images.- Learning by Integrating Information Within and Across Fixations.- Feature Conjunctions in Visual Search.- A Biologically Motivated System for Unconstrained Online Learning of Visual Objects.- Second-Order (Non-Fourier) Attention-Based Face Detection.- Requirements for the Transmission of Streaming Video in Mobile Wireless Networks.- Wavelet Based Estimation of Saliency Maps in Visual Attention Algorithms.- Vision and Image Processing (I).- Selective Tuning: Feature Binding Through Selective Attention.- Rotation Invariant Recognition of Road Signs with Ensemble of 1-NN Neural Classifiers.- Computer Aided Classification of Mammographic Tissue Using Independent Component Analysis and Support Vector Machines.- Growing Neural Gas for Vision Tasks with Time Restrictions.- A Fixed-Point Algorithm of Topographic ICA.- Image Compression by Vector Quantization with Recurrent Discrete Networks.- Vision and Image Processing (II).- Feature Extraction Using Class-Augmented Principal Component Analysis (CA-PCA).- A Comparative Study of the Objectionable Video Classification Approaches Using Single and Group Frame Features.- Human Facial Expression Recognition Using Hybrid Network of PCA and RBFN.- Extracting Motion Primitives from Natural Handwriting Data.- Including Metric Space Topology in Neural Networks Training by Ordering Patterns.- Computational Finance and Economics (Special Session).- A Technical Trading Indicator Based on Dynamical Consistent Neural Networks.- Testing the Random Walk Hypothesis with Neural Networks.- Financial Application of Neural Networks: Two Case Studies in Greece.- Credit Risk Analysis Using a Reliability-Based Neural Network Ensemble Model.- Competitive and Collaborative Mixtures of Experts for Financial Risk Analysis.- Neural Computing in Energy Engineering (Special Session).- Kernel Regression Based Short-Term Load Forecasting.- Electricity Load Forecasting Using Self Organizing Maps.- A Hybrid Neural Model in Long-Term Electrical Load Forecasting.- Application of Radial Basis Function Networks for Wind Power Forecasting.- The Application of Neural Networks to Electric Power Grid Simulation.- Early Detection of Winding Faults in Windmill Generators Using Wavelet Transform and ANN Classification.- Combining Artificial Neural Networks and Heuristic Rules in a Hybrid Intelligent Load Forecast System.- New Phenemenon on Power Transformers and Fault Identification Using Artificial Neural Networks.- Applications to Biomedicine and Bioinformatics.- Neural Network Based Algorithm for Radiation Dose Evaluation in Heterogeneous Environments.- Exploring the Intrinsic Structure of Magnetic Resonance Spectra Tumor Data Based on Independent Component Analysis and Correlation Analysis.- Fusing Biomedical Multi-modal Data for Exploratory Data Analysis.- Semi-supervised Significance Score of Differential Gene Expressions.- Semi Supervised Fuzzy Clustering Networks for Constrained Analysis of Time-Series Gene Expression Data.- Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts.- Tree-Dependent Components of Gene Expression Data for Clustering.- Applications to Security and Market Analysis.- A Neural Model in Anti-spam Systems.- A Neural Model in Intrusion Detection Systems.- Improved Kernel Based Intrusion Detection System.- Testing the Fraud Detection Ability of Different User Profiles by Means of FF-NN Classifiers.- Predicting User's Movement with a Combination of Self-Organizing Map and Markov Model.- Learning Manifolds in Forensic Data.- A Comparison of Target Customers in Asian Online Game Markets: Marketing Applications of a Two-Level SOM.- Real World Applications (I).- A Neural Network Approach to Study O3 and PM10 Concentration in Environmental Pollution.- ROC Analysis as a Useful Tool for Performance Evaluation of Artificial Neural Networks.- NewPR-Combining TFIDF with Pagerank.- A Fast Algorithm for Words Reordering Based on Language Model.- Phonetic Feature Discovery in Speech Using Snap-Drift Learning.- A New Neuro-Dominance Rule for Single Machine Tardiness Problem with Unequal Release Dates.- Real World Applications (II).- A Competitive Approach to Neural Device Modeling: Support Vector Machines.- Non-destructive Testing for Assessing Structures by Using Soft-Computing.- Neural Unit Element Application for in Use Microwave Circuitry.- An Artificial Neural Network Based Simulation Metamodeling Approach for Dual Resource Constrained Assembly Line.- A Packet Routing Method Using Chaotic Neurodynamics for Complex Networks.
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