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[null,null,"Titolo",null,"Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings Part III / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015"]
[null,null,"ISBN",null,"3-319-26555-5"]
[null,null,"Edizione",null,"[1st ed. 2015.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVII, 710 p. 250 illus. in color.)"]
[null,null,"Collana",null,"Theoretical Computer Science and General Issues, , 2512-2029 ; ; 9491"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Pattern recognition systems"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Automated Pattern Recognition"]
[{"$nulls":4},"Computer Vision"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Theory of Computation"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part III -- Design of an Adaptive Support Vector Regressor Controller for a Spherical Tank System -- 1 Introduction -- 2 Adaptive Online SVR Controller -- 3 Online -SVR for Controller Design -- 4 Simulation Results -- 5 Conclusion -- References -- Robust Tracking Control of Uncertain Nonlinear Systems Using Adaptive Dynamic Programming -- 1 Introduction -- 2 Preliminaries -- 3 Problem Transformation -- 4 Approximate the HJB Solution via ADP -- 5 Simulation Results -- 6 Conclusions -- References -- Moving Target Tracking Based on Pulse Coupled Neural Network and Optical Flow -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Optical Flow -- 2.2 Pulse-Coupled Neural "]
[{"$nulls":4},"Network -- 2.3 PCNN Fusion Based on Optical Flow -- 2.4 Topological Property -- 3 Algorithm Structure -- 4 Experimental Results -- 4.1 Database -- 4.2 Attention Detection Effects -- 4.3 Comparison of Attention Detection Models -- 5 Conclusion -- References -- Efficient Motor Babbling Using Variance Predictions from a Recurrent Neural Network -- 1 Introduction -- 2 Exploratory Motor Babbling -- 2.1 Stochastic Continuous Time-Scales Recurrent Neural Networks -- 2.2 Learning Process of Exploratory Motor Babbling -- 3 Experimental Setup -- 3.1 Robot Model in Simulation -- 3.2 Design of Motor Babbling -- 3.3 Experimental Evaluation -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- Distributed Control for Nonlinear Time-Delayed Multi-Agent Systems with Connectivity Preservation Using Neural Networks -- 1 Introduction -- 2 Preliminaries -- 2.1 Graph Theory -- 2.2 Radial Basis Function Neural Network -- 2.3 Problem Statement -- 3 Distributed Control for Nonlinear Time-Delayed Multi-Agent Systems -- 4 Simulation Example -- 5 Conclusion -- References."]
[{"$nulls":4},"Coevolutionary Recurrent Neural Networks for Prediction of Rapid Intensification in Wind Intensity of Tropical Cyclones in the South Pacific Region -- 1 Introduction -- 2 Coevolutionary Recurrent Networks for Rapid Intensification -- 2.1 Recurrent Network Architecture -- 2.2 Cooperative Neuro-Evolutionary Recurrent Networks -- 2.3 Application Problem: Rapid intensification in Cyclones -- 3 Experiments and Results -- 3.1 Analysis of the Dataset -- 3.2 Data Pre-processing -- 3.3 Results -- 3.4 Discussion -- 4 Conclusions and Future Work -- References -- Nonlinear Filtering Based on a Network with Gaussian Kernel Functions -- 1 Introduction -- 2 Nonlinear Filters for Signal Enhancement -- 3 Phase Space Analysis of Noisy Signals -- 4 Nonlinear Filters with Gaussian Kernel Functions -- 5 Simulation -- 6 Conclusion -- References -- Computing Skyline Probabilities on Uncertain Time Series -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Background of Skyline Queries -- 3.1 Skylines on Certain Time Series -- 3.2 Skylines on Uncertain Time Series -- 4 Probabilistic Skyline Answering Algorithm -- 4.1 Obtaining the Skyline -- 4.2 Computing the Skyline Probability -- 5 Experiment Study -- 6 Conclusions -- References -- Probabilistic Prediction of Chaotic Time Series Using Similarity of Attractors and LOOCV Predictable Horizons for Obtaining Plausible Predictions -- 1 Introduction -- 2 Probabilistic Prediction of Chaotic Time Series -- 2.1 Point Prediction of Chaotic Time Series -- 2.2 Probabilistic Prediction -- 3 Numerical Experiments and Analysis -- 3.1 Experimental Settings -- 3.2 Results and Analysis -- 4 Conclusion -- A CAN2 -- References -- Adaptive Threshold for Anomaly Detection Using Time Series Segmentation -- 1 Introduction -- 2 Segmentation and Anomaly Detection -- 3 Adaptive Threshold for Anomaly Detection (ATAD)."]
[{"$nulls":4},"3.1 Adaptive Piecewise Constant Approximation -- 3.2 Description of the Method -- 3.3 Numerical Experiments -- 4 Conclusion and Future Works -- References -- Neuron-Synapse Level Problem Decomposition Method for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction -- 1 Introduction -- 2 Neuron-Synapse Level Problem Decomposition -- 3 Experiments, Results and Discussion -- 3.1 Experimental Setup -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Prediction Interval-Based Control of Nonlinear Systems Using Neural Networks -- 1 Introduction -- 2 PI-based Controller -- 3 Proposed Methodology -- 3.1 Feed-Forward NN Model -- 3.2 PI-based NN Model -- 3.3 PI-based NN Inverse Model (PIC) -- 4 Case Studies -- 5 Results and Discussion -- 6 Conclusion -- References -- Correcting a Class of Complete Selection Bias with "]
[{"$nulls":4},"External Data Based on Importance Weight Estimation -- 1 Introduction -- 2 Bias Correction -- 3 Experiments -- 3.1 Toy Problem -- 3.2 Real-World Data Sets -- 4 Discussion and Conclusion -- References -- Lagrange Programming Neural Network for the l1-norm Constrained Quadratic Minimization -- 1 Introduction -- 2 Background -- 3 LPNN for L1CQM -- 4 Properties of LPNN -- 5 Simulations -- 6 Conclusion -- References -- Multi-Island Competitive Cooperative Coevolution for Real Parameter Global Optimization -- 1 Introduction -- 2 Multi-Island Competitive Cooperative Coevolution -- 2.1 Initialization -- 2.2 Cooperative Coevolution -- 2.3 Competition -- 2.4 Collaboration - Solution Migration -- 3 Simulation and Analysis -- 3.1 Benchmark Problems and Configuration -- 3.2 Results and Analysis -- 3.3 Discussion -- 4 Conclusions and Future Work -- References -- Competitive Island-Based Cooperative Coevolution for Efficient Optimization of Large-Scale Fully-Separable Continuous Functions -- 1 Introduction."]
[{"$nulls":4},"2 Competitive Island Cooperative Coevolution for Fully-Separable Continuous Functions -- 2.1 Initialization -- 2.2 Coevolution in CICC -- 2.3 Competition and Collaboration -- 3 Simulation and Analysis -- 3.1 Problem Decomposition Strategies -- 3.2 Benchmark Problems and Parameter Settings -- 4 Results and Analyses -- 4.1 Competition Between Same Problem Decomposition Strategies -- 4.2 Competition Between Different Problem Decomposition Strategies -- 5 Conclusions and Future Work -- References -- Topic Optimization Method Based on Pointwise Mutual Information -- Abstract -- 1 Introduction -- 2 LDA Based on Point-Wise Mutual Information (PMI-LDA) -- 2.1 Introduction of the LDA Topic Model -- 2.2 PMI-LDA Topic Model -- 3 Topic Evaluation -- 4 Experiments -- 5 Conclusion -- Acknowledgments -- References -- Optimization and Analysis of Parallel Back Propagation Neural Network on GPU Using CUDA -- Abstract -- 1 Introduction -- 2 Parallel Back Propagation Algorithm on GPU -- 3 Optimized Program Framework on GPU -- 4 Experimental Results and Discussion -- 4.1 Data Sets for Experiments -- 4.2 Results of Experiments -- 4.3 Discussion -- 5 Conclusions -- References -- Objective Function of ICA with Smooth Estimation of Kurtosis -- 1 Introduction -- 2 Derivation of Objective Function of ICA -- 2.1 Preliminaries -- 2.2 Estimation of True Distribution -- 2.3 Objective Function -- 3 Optimization Method -- 4 Results -- 5 Conclusion -- References -- FANet: Factor Analysis Neural Network -- 1 Introduction -- 2 Unsupervised Feature Learning via FANet -- 2.1 Normalizing the Input Data -- 2.2 Convolution Layers -- 2.3 Pooling Layers -- 2.4 Analytical Characterization of FANet -- 3 Experiments -- 3.1 Facial Recognition on FERET -- 3.2 Handwritten Digit Recognition on MNIST and MNIST Variations -- 4 Conclusion -- References."]
[{"$nulls":4},"Oscillated Variable Neighborhood Search for Open Vehicle Routing Problem -- Abstract -- 1 Introduction -- 2 Proposed Algorithm -- 3 Experimental Results -- 4 Conclusion -- Acknowledgements -- References -- Non-Line-of-Sight Mitigation via Lagrange Programming Neural Networks in TOA-Based Localization -- 1 Introduction -- 2 Background -- 2.1 Problem Formulation -- 3 Algorithm Development -- 4 Simulation Results -- 5 Conclusion -- References -- Wave-Based Reservoir Computing by Synchronization of Coupled Oscillators -- 1 Introduction -- 2 Wave-Based Reservoir Computing -- 3 Phase Dynamics of Coupled Oscillators -- 3.1 Phase Response Curves -- 3.2 Phase Synchronization -- 4 Function Approximation and Regression by Wave-Based Reservoir Computing -- 4.1 Function Approximation by Two Coupled Oscillators -- 4.2 Functional Regression by an Oscillator Reservoir -- 5 Conclusion -- References -- Hybrid Controller with the "]
[{"$nulls":4},"Combination of FLC and Neural Network-Based IMC for Nonlinear Processes -- 1 Introduction -- 2 Proposed Hybrid Controller -- 2.1 Fuzzy Logic Controller -- 2.2 NN-Based Internal Model Controller -- 2.3 Hybrid Controller -- 3 Methodology -- 3.1 Development of FLC -- 3.2 Development of NN-Based IMC -- 4 Case Study and Experimental Data -- 5 Results and Discussion -- 6 Conclusion -- References -- Comparative Study of Web-Based Gene Expression Analysis Tools for Biomarkers Identification -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 Gene Expression Datasets -- 2.2 Web-Based Gene Expression Analysis Tools -- 2.3 Evaluation -- 3 Results and Discussion -- 3.1 Features Comparison -- 3.2 Gene Markers Comparison -- 3.3 Classification of Selected Gene Markers -- 4 Conclusion -- References -- Eye Can Tell: On the Correlation Between Eye Movement and Phishing Identification -- 1 Introduction -- 2 Related Work -- 3 Proposal -- 4 Experiment Setup."]
[{"$nulls":4},"5 Eye Movement Analysis."]
[null,null,null,"Sommario/riassunto","The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks."]