Artificial neural networks - ICANN 2007 : 17th International Conference, Porto, Portugal, September 9-13, 2007 : proceedings
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書誌事項
Artificial neural networks - ICANN 2007 : 17th International Conference, Porto, Portugal, September 9-13, 2007 : proceedings
（Lecture notes in computer science, 4668-4669）
Springer, c2007
- pt. 1
- pt. 2
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注記
Includes bibliographical references and index
内容説明・目次
- 巻冊次
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pt. 1 ISBN 9783540746898
内容説明
This book is the first of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, September 2007. Coverage includes advances in neural network learning methods, advances in neural network architectures, neural dynamics and complex systems, data analysis, evolutionary computing, agents learning, as well as temporal synchronization and nonlinear dynamics in neural networks.
目次
Learning Theory.- Generalization Error of Automatic Relevance Determination.- On a Singular Point to Contribute to a Learning Coefficient and Weighted Resolution of Singularities.- Improving the Prediction Accuracy of Echo State Neural Networks by Anti-Oja's Learning.- Theoretical Analysis of Accuracy of Gaussian Belief Propagation.- Relevance Metrics to Reduce Input Dimensions in Artificial Neural Networks.- An Improved Greedy Bayesian Network Learning Algorithm on Limited Data.- Incremental One-Class Learning with Bounded Computational Complexity.- Estimating the Size of Neural Networks from the Number of Available Training Data.- A Maximum Weighted Likelihood Approach to Simultaneous Model Selection and Feature Weighting in Gaussian Mixture.- Estimation of Poles of Zeta Function in Learning Theory Using Pade Approximation.- Neural Network Ensemble Training by Sequential Interaction.- Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification.- Advances in Neural Network Learning Methods.- Structure Learning with Nonparametric Decomposable Models.- Recurrent Bayesian Reasoning in Probabilistic Neural Networks.- Resilient Approximation of Kernel Classifiers.- Incremental Learning of Spatio-temporal Patterns with Model Selection.- Accelerating Kernel Perceptron Learning.- Analysis and Comparative Study of Source Separation Performances in Feed-Forward and Feed-Back BSSs Based on Propagation Delays in Convolutive Mixture.- Learning Highly Non-separable Boolean Functions Using Constructive Feedforward Neural Network.- A Fast Semi-linear Backpropagation Learning Algorithm.- Improving the GRLVQ Algorithm by the Cross Entropy Method.- Incremental and Decremental Learning for Linear Support Vector Machines.- An Efficient Method for Pruning the Multilayer Perceptron Based on the Correlation of Errors.- Reinforcement Learning for Cooperative Actions in a Partially Observable Multi-agent System.- Input Selection for Radial Basis Function Networks by Constrained Optimization.- An Online Backpropagation Algorithm with Validation Error-Based Adaptive Learning Rate.- Adaptive Self-scaling Non-monotone BFGS Training Algorithm for Recurrent Neural Networks.- Some Properties of the Gaussian Kernel for One Class Learning.- Improved SOM Learning Using Simulated Annealing.- The Usage of Golden Section in Calculating the Efficient Solution in Artificial Neural Networks Training by Multi-objective Optimization.- Ensemble Learning.- Designing Modular Artificial Neural Network Through Evolution.- Averaged Conservative Boosting: Introducing a New Method to Build Ensembles of Neural Networks.- Selection of Decision Stumps in Bagging Ensembles.- An Ensemble Dependence Measure.- Boosting Unsupervised Competitive Learning Ensembles.- Using Fuzzy, Neural and Fuzzy-Neural Combination Methods in Ensembles with Different Levels of Diversity.- Spiking Neural Networks.- SpikeStream: A Fast and Flexible Simulator of Spiking Neural Networks.- Evolutionary Multi-objective Optimization of Spiking Neural Networks.- Building a Bridge Between Spiking and Artificial Neural Networks.- Clustering of Nonlinearly Separable Data Using Spiking Neural Networks.- Implementing Classical Conditioning with Spiking Neurons.- Advances in Neural Network Architectures.- Deformable Radial Basis Functions.- Selection of Basis Functions Guided by the L2 Soft Margin.- Extended Linear Models with Gaussian Prior on the Parameters and Adaptive Expansion Vectors.- Functional Modelling of Large Scattered Data Sets Using Neural Networks.- Stacking MF Networks to Combine the Outputs Provided by RBF Networks.- Neural Network Processing for Multiset Data.- The Introduction of Time-Scales in Reservoir Computing, Applied to Isolated Digits Recognition.- Partially Activated Neural Networks by Controlling Information.- CNN Based Hole Filler Template Design Using Numerical Integration Techniques.- Impact of Shrinking Technologies on the Activation Function of Neurons.- Rectangular Basis Functions Applied to Imbalanced Datasets.- Qualitative Radial Basis Function Networks Based on Distance Discretization for Classification Problems.- A Control Approach to a Biophysical Neuron Model.- Integrate-and-Fire Neural Networks with Monosynaptic-Like Correlated Activity.- Multi-dimensional Recurrent Neural Networks.- FPGA Implementation of an Adaptive Stochastic Neural Model.- Neural Dynamics and Complex Systems.- Global Robust Stability of Competitive Neural Networks with Continuously Distributed Delays and Different Time Scales.- Nonlinear Dynamics Emerging in Large Scale Neural Networks with Ontogenetic and Epigenetic Processes.- Modeling of Dynamics Using Process State Projection on the Self Organizing Map.- Fixed Points of the Abe Formulation of Stochastic Hopfield Networks.- Visualization of Dynamics Using Local Dynamic Modelling with Self Organizing Maps.- Comparison of Echo State Networks with Simple Recurrent Networks and Variable-Length Markov Models on Symbolic Sequences.- Data Analysis.- Data Fusion and Auto-fusion for Quantitative Structure-Activity Relationship (QSAR).- Cluster Domains in Binary Minimization Problems.- MaxSet: An Algorithm for Finding a Good Approximation for the Largest Linearly Separable Set.- Generalized Softmax Networks for Non-linear Component Extraction.- Stochastic Weights Reinforcement Learning for Exploratory Data Analysis.- Post Nonlinear Independent Subspace Analysis.- Estimation.- Algebraic Geometric Study of Exchange Monte Carlo Method.- Solving Deep Memory POMDPs with Recurrent Policy Gradients.- Soft Clustering for Nonparametric Probability Density Function Estimation.- Vector Field Approximation by Model Inclusive Learning of Neural Networks.- Spectral Measures for Kernel Matrices Comparison.- A Novel and Efficient Method for Testing Non Linear Separability.- A One-Step Unscented Particle Filter for Nonlinear Dynamical Systems.- Spatial and Spatio-Temporal Learning.- Spike-Timing-Dependent Synaptic Plasticity to Learn Spatiotemporal Patterns in Recurrent Neural Networks.- A Distributed Message Passing Algorithm for Sensor Localization.- An Analytical Model of Divisive Normalization in Disparity-Tuned Complex Cells.- Evolutionary Computing.- Automatic Design of Modular Neural Networks Using Genetic Programming.- Blind Matrix Decomposition Via Genetic Optimization of Sparseness and Nonnegativity Constraints.- Meta Learning, Agents Learning.- Meta Learning Intrusion Detection in Real Time Network.- Active Learning to Support the Generation of Meta-examples.- Co-learning and the Development of Communication.- Complex-Valued Neural Networks (Special Session).- Models of Orthogonal Type Complex-Valued Dynamic Associative Memories and Their Performance Comparison.- Dynamics of Discrete-Time Quaternionic Hopfield Neural Networks.- Neural Learning Algorithms Based on Mappings: The Case of the Unitary Group of Matrices.- Optimal Learning Rates for Clifford Neurons.- Solving Selected Classification Problems in Bioinformatics Using Multilayer Neural Network Based on Multi-Valued Neurons (MLMVN).- Error Reduction in Holographic Movies Using a Hybrid Learning Method in Coherent Neural Networks.- Temporal Synchronization and Nonlinear Dynamics in Neural Networks (Special Session).- Sparse and Transformation-Invariant Hierarchical NMF.- Zero-Lag Long Range Synchronization of Neurons Is Enhanced by Dynamical Relaying.- Polynomial Cellular Neural Networks for Implementing the Game of Life.- Deterministic Nonlinear Spike Train Filtered by Spiking Neuron Model.- The Role of Internal Oscillators for the One-Shot Learning of Complex Temporal Sequences.- Clustering Limit Cycle Oscillators by Spectral Analysis of the Synchronisation Matrix with an Additional Phase Sensitive Rotation.- Control and Synchronization of Chaotic Neurons Under Threshold Activated Coupling.- Neuronal Multistability Induced by Delay.
- 巻冊次
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pt. 2 ISBN 9783540746935
内容説明
This book is the second of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007. It features contributions related to computational neuroscience, neurocognitive studies, applications in biomedicine and bioinformatics, pattern recognition, self-organization, text mining and internet applications, signal and times series processing, vision and image processing, robotics, control, and more.
目次
Computational Neuroscience, Neurocognitive Studies.- A Marker-Based Model for the Ontogenesis of Routing Circuits.- A Neural Network for the Analysis of Multisensory Integration in the Superior Colliculus.- Neurotransmitter Fields.- SimBa: A Fuzzy Similarity-Based Modelling Framework for Large-Scale Cerebral Networks.- A Direct Measurement of Internal Model Learning Rates in a Visuomotor Tracking Task.- Spatial and Temporal Selectivity of Hippocampal CA3 and Its Contribution to Sequence Disambiguation.- Lateral and Elastic Interactions: Deriving One Form from Another.- Applications in Biomedicine and Bioinformatics.- A Survey on Use of Soft Computing Methods in Medicine.- Exploiting Blind Matrix Decomposition Techniques to Identify Diagnostic Marker Genes.- Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping.- Identifying Binding Sites in Sequential Genomic Data.- On the Combination of Dissimilarities for Gene Expression Data Analysis.- A Locally Recurrent Globally Feed-Forward Fuzzy Neural Network for Processing Lung Sounds.- Learning Temporally Stable Representations from Natural Sounds: Temporal Stability as a General Objective Underlying Sensory Processing.- Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression.- Classifying EEG Data into Different Memory Loads Across Subjects.- Information Theoretic Derivations for Causality Detection: Application to Human Gait.- Pattern Recognition.- Template Matching for Large Transformations.- Fuzzy Classifiers Based on Kernel Discriminant Analysis.- An Efficient Search Strategy for Feature Selection Using Chow-Liu Trees.- Face Recognition Using Parzenfaces.- A Comparison of Features in Parts-Based Object Recognition Hierarchies.- An Application of Recurrent Neural Networks to Discriminative Keyword Spotting.- Spatiostructural Features for Recognition of Online Handwritten Characters in Devanagari and Tamil Scripts.- An Improved Version of the Wrapper Feature Selection Method Based on Functional Decomposition.- Parallel-Series Perceptrons for the Simultaneous Determination of Odor Classes and Concentrations.- Probabilistic Video-Based Gesture Recognition Using Self-organizing Feature Maps.- Unbiased SVM Density Estimation with Application to Graphical Pattern Recognition.- Neural Mechanisms for Mid-Level Optical Flow Pattern Detection.- Data Clustering.- Split-Merge Incremental LEarning (SMILE) of Mixture Models.- Least-Mean-Square Training of Cluster-Weighted Modeling.- Identifying the Underlying Hierarchical Structure of Clusters in Cluster Analysis.- Clustering Evaluation in Feature Space.- A Topology-Independent Similarity Measure for High-Dimensional Feature Spaces.- Self-organization.- Fuzzy Labeled Self-organizing Map with Kernel-Based Topographic Map Formation.- Self-organizing Maps of Spiking Neurons with Reduced Precision of Correlated Firing.- Visualising Class Distribution on Self-organising Maps.- Self-organizing Maps with Refractory Period.- Improving the Correlation Hunting in a Large Quantity of SOM Component Planes.- A Dynamical Model for Receptive Field Self-organization in V1 Cortical Columns.- Text Mining and Internet Applications.- Meta-evolution Strategy to Focused Crawling on Semantic Web.- Automated Text Categorization Based on Readability Fingerprints.- Personalized Web Page Filtering Using a Hopfield Neural Network.- Robust Text Classification Using a Hysteresis-Driven Extended SRN.- Semi-supervised Metrics for Textual Data Visualization.- Topology Aware Internet Traffic Forecasting Using Neural Networks.- Signal and Times Series Processing.- Boosting Algorithm to Improve a Voltage Waveform Classifier Based on Artificial Neural Network.- Classification of Temporal Data Based on Self-organizing Incremental Neural Network.- Estimating the Impact of Shocks with Artificial Neural Networks.- Greedy KPCA in Biomedical Signal Processing.- The Use of Artificial Neural Networks in the Speech Understanding Model - SUM.- On Incorporating Seasonal Information on Recursive Time Series Predictors.- Can Neural Networks Learn the "Head and Shoulders" Technical Analysis Price Pattern? Towards a Methodology for Testing the Efficient Market Hypothesis.- Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space.- Vision and Image Processing.- Content-Based Image Retrieval by Combining Genetic Algorithm and Support Vector Machine.- Global and Local Preserving Feature Extraction for Image Categorization.- Iris Recognition for Biometric Personal Identification Using Neural Networks.- No-Reference Quality Assessment of JPEG Images by Using CBP Neural Networks.- A Bio-inspired Connectionist Approach for Motion Description Through Sequences of Images.- Color Object Recognition in Real-World Scenes.- Estimation of Pointing Poses on Monocular Images with Neural Techniques - An Experimental Comparison.- Real-Time Foreground-Background Segmentation Using Adaptive Support Vector Machine Algorithm.- Edge-Preserving Bayesian Image Superresolution Based on Compound Markov Random Fields.- Robotics, Control.- A Neurofuzzy Controller for a Single Link Flexible Manipulator.- Suboptimal Nonlinear Predictive Control with Structured Neural Models.- Neural Dynamics Based Exploration Algorithm for a Mobile Robot.- Neural Models in Computationally Efficient Predictive Control Cooperating with Economic Optimisation.- Event Detection and Localization in Mobile Robot Navigation Using Reservoir Computing.- Model Reference Control Using CMAC Neural Networks.- Real World Applications.- A Three-Stage Approach Based on the Self-organizing Map for Satellite Image Classification.- Performance Analysis of MLP-Based Radar Detectors in Weibull-Distributed Clutter with Respect to Target Doppler Frequency.- Local Positioning System Based on Artificial Neural Networks.- An Adaptive Neuro-Fuzzy Inference System for Calculation Resonant Frequency and Input Resistance of Microstrip Dipole Antenna.- GARCH Processes with Non-parametric Innovations for Market Risk Estimation.- Forecasting Portugal Global Load with Artificial Neural Networks.- Using Genetic Algorithm to Develop a Neural-Network-Based Load Forecasting.- Separation and Recognition of Multiple Sound Source Using Pulsed Neuron Model.- Text-Independent Speaker Authentication with Spiking Neural Networks.- Interferences in the Transformation of Reference Frames During a Posture Imitation Task.- Combined Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System for Improving a Short-Term Electric Load Forecasting.- A MLP Solver for First and Second Order Partial Differential Equations.- Independent Component Analysis.- A Two-Layer ICA-Like Model Estimated by Score Matching.- Testing Component Independence Using Data Compressors.- Graphs.- K-Pages Graph Drawing with Multivalued Neural Networks.- Recursive Principal Component Analysis of Graphs.- A Method to Estimate the Graph Structure for a Large MRF Model.- Emotion and Attention: Empirical Findings Neural Models (Special Session).- Neural Substructures for Appraisal in Emotion: Self-esteem and Depression.- The Link Between Temporal Attention and Emotion: A Playground for Psychology, Neuroscience, and Plausible Artificial Neural Networks.- Inferring Cognition from fMRI Brain Images.- Modelling the N2pc and Its Interaction with Value.- Biasing Neural Networks Towards Exploration or Exploitation Using Neuromodulation.- Understanding and Creating Cognitive Systems (Special Session).- A Simple Model of Cortical Activations During Both Observation and Execution of Reach-to-Grasp Movements.- A Cognitive Model That Describes the Influence of Prior Knowledge on Concept Learning.- Developing Concept Representations.- Self-perturbation and Homeostasis in Embodied Recurrent Neural Networks: A Meta-model and Some Explorations with Mechanisms for Sensorimotor Coordination.- An Oscillatory Model for Multimodal Processing of Short Language Instructions.- Towards Understanding of Natural Language: Neurocognitive Inspirations.- A Computational Model of Metaphor Understanding Consisting of Two Processes.- A Novel Novelty Detector.
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