Description
Springer Artificial Neural Networks - Icann 2009 19Th International Conference 2009 Edition by Cesare Alippi Marios M. Polycarpou Christos Panayiotou Georgios Ellinas
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. Table of contents : 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.show more