Artificial neural networks - ICANN 2009 : 19th international conference, Limassol, Cyprus, September 14-17, 2009 : proceedings
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書誌事項
Artificial neural networks - ICANN 2009 : 19th international conference, Limassol, Cyprus, September 14-17, 2009 : proceedings
（Lecture notes in computer science, 5768-5769）
Springer, c2009
- pt. 1
- pt. 2
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Includes bibliographical references and index
内容説明・目次
- 巻冊次
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pt. 1 ISBN 9783642042737
内容説明
This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14-17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.
目次
Learning Algorithms.- Mutual Information Based Initialization of Forward-Backward Search for Feature Selection in Regression Problems.- Kernel Learning for Local Learning Based Clustering.- Projective Nonnegative Matrix Factorization with ?-Divergence.- Active Generation of Training Examples in Meta-Regression.- A Maximum-Likelihood Connectionist Model for Unsupervised Learning over Graphical Domains.- Local Feature Selection for the Relevance Vector Machine Using Adaptive Kernel Learning.- MINLIP: Efficient Learning of Transformation Models.- Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data.- Optimal Training Sequences for Locally Recurrent Neural Networks.- Statistical Instance-Based Ensemble Pruning for Multi-class Problems.- Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes.- Mixing Different Search Biases in Evolutionary Learning Algorithms.- Semi-supervised Learning for Regression with Co-training by Committee.- An Analysis of Meta-learning Techniques for Ranking Clustering Algorithms Applied to Artificial Data.- Probability-Based Distance Function for Distance-Based Classifiers.- Constrained Learning Vector Quantization or Relaxed k-Separability.- Minimization of Quadratic Binary Functional with Additive Connection Matrix.- Mutual Learning with Many Linear Perceptrons: On-Line Learning Theory.- Computational Neuroscience.- Synchrony State Generation in Artificial Neural Networks with Stochastic Synapses.- Coexistence of Cell Assemblies and STDP.- Controlled and Automatic Processing in Animals and Machines with Application to Autonomous Vehicle Control.- Multiple Sound Source Localisation in Reverberant Environments Inspired by the Auditory Midbrain.- A Model of Neuronal Specialization Using Hebbian Policy-Gradient with "Slow" Noise.- How Bursts Shape the STDP Curve in the Presence/Absence of GABAergic Inhibition.- Optimizing Generic Neural Microcircuits through Reward Modulated STDP.- Calcium Responses Model in Striatum Dependent on Timed Input Sources.- Independent Component Analysis Aided Diagnosis of Cuban Spino Cerebellar Ataxia 2.- Hippocampus, Amygdala and Basal Ganglia Based Navigation Control.- A Framework for Simulation and Analysis of Dynamically Organized Distributed Neural Networks.- Continuous Attractors of Lotka-Volterra Recurrent Neural Networks.- Learning Complex Population-Coded Sequences.- Structural Analysis on STDP Neural Networks Using Complex Network Theory.- Time Coding of Input Strength Is Intrinsic to Synapses with Short Term Plasticity.- Information Processing and Timing Mechanisms in Vision.- Review of Neuron Types in the Retina: Information Models for Neuroengineering.- Brain Electric Microstate and Perception of Simultaneously Audiovisual Presentation.- A Model for Neuronal Signal Representation by Stimulus-Dependent Receptive Fields.- Hardware Implementations and Embedded Systems.- Area Chip Consumption by a Novel Digital CNN Architecture for Pattern Recognition.- Multifold Acceleration of Neural Network Computations Using GPU.- Training Recurrent Neural Network Using Multistream Extended Kalman Filter on Multicore Processor and Cuda Enabled Graphic Processor Unit.- A Non-subtraction Configuration of Self-similitude Architecture for Multiple-Resolution Edge-Filtering CMOS Image Sensor.- Current-Mode Computation with Noise in a Scalable and Programmable Probabilistic Neural VLSI System.- Minimising Contrastive Divergence with Dynamic Current Mirrors.- Spiking Neural Network Self-configuration for Temporal Pattern Recognition Analysis.- Image Recognition in Analog VLSI with On-Chip Learning.- Behavior Modeling by Neural Networks.- Statistical Parameter Identification of Analog Integrated Circuit Reverse Models.- A New FGMOST Euclidean Distance Computational Circuit Based on Algebraic Mean of the Input Potentials.- FPGA Implementation of Support Vector Machines for 3D Object Identification.- Reconfigurable MAC-Based Architecture for Parallel Hardware Implementation on FPGAs of Artificial Neural Networks Using Fractional Fixed Point Representation.- Self Organization.- A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means.- Image Theft Detection with Self-Organising Maps.- Improved Kohonen Feature Map Associative Memory with Area Representation for Sequential Analog Patterns.- Surface Reconstruction Method Based on a Growing Self-Organizing Map.- Micro-SOM: A Linear-Time Multivariate Microaggregation Algorithm Based on Self-Organizing Maps.- Identifying Clusters Using Growing Neural Gas: First Results.- Hierarchical Architecture with Modular Network SOM and Modular Reinforcement Learning.- Hybrid Systems for River Flood Forecasting Using MLP, SOM and Fuzzy Systems.- Topographic Mapping of Astronomical Light Curves via a Physically Inspired Probabilistic Model.- Generalized Self-Organizing Mixture Autoregressive Model for Modeling Financial Time Series.- Self-Organizing Map Simulations Confirm Similarity of Spatial Correlation Structure in Natural Images and Cortical Representations.- Intelligent Control and Adaptive Systems.- Height Defuzzification Method on L ??? Space.- An Additive Reinforcement Learning.- Neural Spike Suppression by Adaptive Control of an Unknown Steady State.- Combined Mechanisms of Internal Model Control and Impedance Control under Force Fields.- Neural Network Control of Unknown Nonlinear Systems with Efficient Transient Performance.- High-Order Fuzzy Switching Neural Networks: Application to the Tracking Control of a Class of Uncertain SISO Nonlinear Systems.- Neural and Hybrid Architectures.- A Guide for the Upper Bound on the Number of Continuous-Valued Hidden Nodes of a Feed-Forward Network.- Comparative Study of the CG and HBF ODEs Used in the Global Minimization of Nonconvex Functions.- On the Knowledge Organization in Concept Formation: An Exploratory Cognitive Modeling Study.- Dynamics of Incremental Learning by VSF-Network.- Kernel CMAC with Reduced Memory Complexity.- Model Complexity of Neural Networks and Integral Transforms.- Function Decomposition Network.- Improved Storage Capacity in Correlation Matrix Memories Storing Fixed Weight Codes.- Multiagent Reinforcement Learning with Spiking and Non-Spiking Agents in the Iterated Prisoner's Dilemma.- Unsupervised Learning in Reservoir Computing: Modeling Hippocampal Place Cells for Small Mobile Robots.- Switching Hidden Markov Models for Learning of Motion Patterns in Videos.- Multimodal Belief Integration by HMM/SVM-Embedded Bayesian Network: Applications to Ambulating PC Operation by Body Motions and Brain Signals.- A Neural Network Model of Metaphor Generation with Dynamic Interaction.- Almost Random Projection Machine.- Optimized Learning Vector Quantization Classifier with an Adaptive Euclidean Distance.- Efficient Parametric Adjustment of Fuzzy Inference System Using Error Backpropagation Method.- Neuro-fuzzy Rough Classifier Ensemble.- Combining Feature Selection and Local Modelling in the KDD Cup 99 Dataset.- An Automatic Parameter Adjustment Method of Pulse Coupled Neural Network for Image Segmentation.- Pattern Identification by Committee of Potts Perceptrons.- Support Vector Machine.- Is Primal Better Than Dual.- A Fast BMU Search for Support Vector Machine.- European Option Pricing by Using the Support Vector Regression Approach.- Learning SVMs from Sloppily Labeled Data.- The GMM-SVM Supervector Approach for the Recognition of the Emotional Status from Speech.- A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems.- Spanning SVM Tree for Personalized Transductive Learning.- Improving Text Classification Performance with Incremental Background Knowledge.- Empirical Study of the Universum SVM Learning for High-Dimensional Data.- Relevance Feedback for Content-Based Image Retrieval Using Support Vector Machines and Feature Selection.- Recurrent Neural Network.- Understanding the Principles of Recursive Neural Networks: A Generative Approach to Tackle Model Complexity.- An EM Based Training Algorithm for Recurrent Neural Networks.- Modeling D st with Recurrent EM Neural Networks.- On the Quantification of Dynamics in Reservoir Computing.- Solving the CLM Problem by Discrete-Time Linear Threshold Recurrent Neural Networks.- Scalable Neural Networks for Board Games.- Reservoir Size, Spectral Radius and Connectivity in Static Classification Problems.
- 巻冊次
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pt. 2 ISBN 9783642042768
内容説明
This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14-17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.
目次
Neuroinformatics and Bioinformatics.- Epileptic Seizure Prediction and the Dimensionality Reduction Problem.- Discovering Diagnostic Gene Targets and Early Diagnosis of Acute GVHD Using Methods of Computational Intelligence over Gene Expression Data.- Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data.- A Computational Retina Model and Its Self-adjustment Property.- Cognitive Machines.- Mental Simulation, Attention and Creativity.- BSDT Atom of Consciousness Model, AOCM: The Unity and Modularity of Consciousness.- Generalized Simulated Annealing and Memory Functioning in Psychopathology.- Algorithms for Structural and Dynamical Polychronous Groups Detection.- Logics and Networks for Human Reasoning.- Data Analysis and Pattern Recognition.- Simbed: Similarity-Based Embedding.- PCA-Based Representations of Graphs for Prediction in QSAR Studies.- Feature Extraction Using Linear and Non-linear Subspace Techniques.- Classification Based on Combination of Kernel Density Estimators.- Joint Approximate Diagonalization Utilizing AIC-Based Decision in the Jacobi Method.- Newtonian Spectral Clustering.- Bidirectional Clustering of MLP Weights for Finding Nominally Conditioned Polynomials.- Recognition of Properties by Probabilistic Neural Networks.- On the Use of the Adjusted Rand Index as a Metric for Evaluating Supervised Classification.- Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning.- Kernel Alignment k-NN for Human Cancer Classification Using the Gene Expression Profiles.- Convex Mixture Models for Multi-view Clustering.- Strengthening the Forward Variable Selection Stopping Criterion.- Features and Metric from a Classifier Improve Visualizations with Dimension Reduction.- Fuzzy Cluster Validation Using the Partition Negentropy Criterion.- Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling.- Using Kernel Basis with Relevance Vector Machine for Feature Selection.- Acquiring and Classifying Signals from Nanopores and Ion-Channels.- Hand-Drawn Shape Recognition Using the SVM'ed Kernel.- Selective Attention Improves Learning.- Signal and Time Series Processing.- Multi-stage Algorithm Based on Neural Network Committee for Prediction and Search for Precursors in Multi-dimensional Time Series.- Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction.- Identifying Customer Profiles in Power Load Time Series Using Spectral Clustering.- Transformation from Complex Networks to Time Series Using Classical Multidimensional Scaling.- Predicting the Occupancy of the HF Amateur Service with Neural Network Ensembles.- An Associated-Memory-Based Stock Price Predictor.- A Case Study of ICA with Multi-scale PCA of Simulated Traffic Data.- Decomposition Methods for Detailed Analysis of Content in ERP Recordings.- Outlier Analysis in BP/RP Spectral Bands.- ANNs and Other Machine Learning Techniques in Modelling Models' Uncertainty.- Comparison of Adaptive Algorithms for Significant Feature Selection in Neural Network Based Solution of the Inverse Problem of Electrical Prospecting.- Efficient Optimization of the Parameters of LS-SVM for Regression versus Cross-Validation Error.- Applications.- Noiseless Independent Factor Analysis with Mixing Constraints in a Semi-supervised Framework. Application to Railway Device Fault Diagnosis.- Speech Hashing Algorithm Based on Short-Time Stability.- A New Method for Complexity Reduction of Neuro-fuzzy Systems with Application to Differential Stroke Diagnosis.- LS Footwear Database - Evaluating Automated Footwear Pattern Analysis.- Advanced Integration of Neural Networks for Characterizing Voids in Welded Strips.- Connectionist Models for Formal Knowledge Adaptation.- Modeling Human Operator Controlling Process in Different Environments.- Discriminating between V and N Beats from ECGs Introducing an Integrated Reduced Representation along with a Neural Network Classifier.- Mental Tasks Classification for a Noninvasive BCI Application.- Municipal Creditworthiness Modelling by Radial Basis Function Neural Networks and Sensitive Analysis of Their Input Parameters.- A Comparison of Three Methods with Implicit Features for Automatic Identification of P300s in a BCI.- Neural Dynamics and Complex Systems.- Computing with Probabilistic Cellular Automata.- Delay-Induced Hopf Bifurcation and Periodic Solution in a BAM Network with Two Delays.- Response Properties to Inputs of Memory Pattern Fragments in Three Types of Chaotic Neural Network Models.- Partial Differential Equations Numerical Modeling Using Dynamic Neural Networks.- The Lin-Kernighan Algorithm Driven by Chaotic Neurodynamics for Large Scale Traveling Salesman Problems.- Quadratic Assignment Problems for Chaotic Neural Networks with Dynamical Noise.- Global Exponential Stability of Recurrent Neural Networks with Time-Dependent Switching Dynamics.- Approximation Capability of Continuous Time Recurrent Neural Networks for Non-autonomous Dynamical Systems.- Spectra of the Spike Flow Graphs of Recurrent Neural Networks.- Activation Dynamics in Excitable Maps: Limits to Communication Can Facilitate the Spread of Activity.- Vision and Image Processing.- Learning Features by Contrasting Natural Images with Noise.- Feature Selection for Neural-Network Based No-Reference Video Quality Assessment.- Learning from Examples to Generalize over Pose and Illumination.- Semi-supervised Learning with Constraints for Multi-view Object Recognition.- Large-Scale Real-Time Object Identification Based on Analytic Features.- Estimation Method of Motion Fields from Images by Model Inclusive Learning of Neural Networks.- Hybrid Neural Systems for Reduced-Reference Image Quality Assessment.- Representing Images with ? 2 Distance Based Histograms of SIFT Descriptors.- Modelling Image Complexity by Independent Component Analysis, with Application to Content-Based Image Retrieval.- Adaptable Neural Networks for Objects' Tracking Re-initialization.- Lattice Independent Component Analysis for fMRI Analysis.- Adaptive Feature Transformation for Image Data from Non-stationary Processes.- Bio-inspired Connectionist Architecture for Visual Detection and Refinement of Shapes.- Neuro-Evolution and Hybrid Techniques for Mobile Agents Control.- Evolving Memory Cell Structures for Sequence Learning.- Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning.- Combining Multiple Inputs in HyperNEAT Mobile Agent Controller.- Evolving Spiking Neural Parameters for Behavioral Sequences.- Robospike Sensory Processing for a Mobile Robot Using Spiking Neural Networks.- Neural Control, Planning and Robotics Applications.- Basis Decomposition of Motion Trajectories Using Spatio-temporal NMF.- An Adaptive NN Controller with Second Order SMC-Based NN Weight Update Law for Asymptotic Tracking.- Optimizing Control by Robustly Feasible Model Predictive Control and Application to Drinking Water Distribution Systems.- Distributed Control over Networks Using Smoothing Techniques.- Trajectory Tracking of a Nonholonomic Mobile Robot Considering the Actuator Dynamics: Design of a Neural Dynamic Controller Based on Sliding Mode Theory.- Tracking with Multiple Prediction Models.- Sliding Mode Control for Trajectory Tracking Problem - Performance Evaluation.- Bilinear Adaptive Parameter Estimation in Fuzzy Cognitive Networks.- Intelligent Tools and Methods for Multimedia Annotation.- AM-FM Texture Image Analysis of the Intima and Media Layers of the Carotid Artery.- Unsupervised Clustering of Clickthrough Data for Automatic Annotation of Multimedia Content.- Object Classification Using the MPEG-7 Visual Descriptors: An Experimental Evaluation Using State of the Art Data Classifiers.- MuLVAT: A Video Annotation Tool Based on XML-Dictionaries and Shot Clustering.- Multimodal Sparse Features for Object Detection.- Critical Infrastructure Systems.- Multiple Kernel Learning of Environmental Data. Case Study: Analysis and Mapping of Wind Fields.- Contributor Diagnostics for Anomaly Detection.- Indoor Localization Using Neural Networks with Location Fingerprints.- Distributed Faulty Sensor Detection in Sensor Networks.- Detection of Failures in Civil Structures Using Artificial Neural Networks.- Congestion Control in Autonomous Decentralized Networks Based on the Lotka-Volterra Competition Model.
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