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Artificial neural networks - ICANN 2009 : 19th international conference, Limassol, Cypros, September 14-17, 2009 : proceedings

Author: Cesare Alippi
Publisher: Berlin ; New York : Springer, ©2009.
Series: Lecture notes in computer science, 5768-5769.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Database:WorldCat
Summary:
This two volume set LNCS 5768 and LNCS 5769 constitutes the refereed proceedings of the 19th International Conference on Artificial Neural Networks, ICANN 2009, held in Limassol, Cyprus, in September 2009. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The first volume is divided in topical sections on learning algorithms; computational neuroscience;  Read more...
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Genre/Form: Electronic books
Conference papers and proceedings
Congresses
Additional Physical Format: Print version:
International Conference on Artificial Neural Networks (European Neural Network Society) (19th : 2009 : Limassol, Cyprus).
Artificial neural networks, ICANN 2009.
Berlin ; New York : Springer, ©2009
(DLC) 2009933887
(OCoLC)436030769
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Cesare Alippi
ISBN: 9783642042744 3642042740 9783642042775 3642042775
OCLC Number: 488855048
Description: 1 online resource (2 volumes) : illustrations.
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.
Series Title: Lecture notes in computer science, 5768-5769.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Responsibility: Cesare Alippi [and others] (eds.).

Abstract:

This two volume set LNCS 5768 and LNCS 5769 constitutes the refereed proceedings of the 19th International Conference on Artificial Neural Networks, ICANN 2009, held in Limassol, Cyprus, in September 2009. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The first volume is divided in topical sections on learning algorithms; computational neuroscience; hardware implementations and embedded systems;self organization; intelligent control and adaptive systems; neural and hybrid architectures; support vector machine; and recurrent neural network.

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