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Advances in Neural Networks -- ISNN 2010

  • Kartonierter Einband
  • 792 Seiten
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This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010... Weiterlesen
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This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has become a well-established series of popular and high-quality conferences on neural computation and its applications. ISNN aims at providing a platform for scientists, researchers, engineers, as well as students to gather together to present and discuss the latest progresses in neural networks, and applications in diverse areas. Nowadays, the field of neural networks has been fostered far beyond the traditional artificial neural networks. This year, ISNN 2010 received 591 submissions from more than 40 countries and regions. Based on rigorous reviews, 170 papers were selected for publication in the proceedings. The papers collected in the proceedings cover a broad spectrum of fields, ranging from neurophysiological experiments, neural modeling to extensions and applications of neural networks. We have organized the papers into two volumes based on their topics. The first volume, entitled Advances in Neural Networks- ISNN 2010, Part 1, covers the following topics: neurophysiological foundation, theory and models, learning and inference, neurodynamics. The second volume en- tled Advance in Neural Networks ISNN 2010, Part 2 covers the following five topics: SVM and kernel methods, vision and image, data mining and text analysis, BCI and brain imaging, and applications.


This book and its sister volume constitutes the proceedings of the 7th International Symposium on Neural Networks, ISNN 2010, held in Shanghai, China, June 6-9, 2010. The 170 revised full papers of Part I and Part II were carefully selected from 591 submissions and focus on topics such as Neurophysiological Foundation, Theory and Models, Learning and Inference, and Neurodynamics. The second volume, Part II (LNCS 6064) covers the following 5 topics: SVM and Kernel Methods, Vision and Image, Data Mining and Text Analysis, BCI and Brain Imaging, and applications.

Neurophysiological Foundation.- Stimulus-Dependent Noise Facilitates Tracking Performances of Neuronal Networks.- Range Parameter Induced Bifurcation in a Single Neuron Model with Delay-Dependent Parameters.- Messenger RNA Polyadenylation Site Recognition in Green Alga Chlamydomonas Reinhardtii.- A Study to Neuron Ensemble of Cognitive Cortex ISI Coding Represent Stimulus.- STDP within NDS Neurons.- Synchronized Activities among Retinal Ganglion Cells in Response to External Stimuli.- Novel Method to Discriminate Awaking and Sleep Status in Light of the Power Spectral Density.- Current Perception Threshold Measurement via Single Channel Electroencephalogram Based on Confidence Algorithm.- Electroantennogram Obtained from Honeybee Antennae for Odor Detection.- A Possible Mechanism for Controlling Timing Representation in the Cerebellar Cortex.- Theory and Models.- Parametric Sensitivity and Scalability of k-Winners-Take-All Networks with a Single State Variable and Infinity-Gain Activation Functions.- Extension of the Generalization Complexity Measure to Real Valued Input Data Sets.- A New Two-Step Gradient-Based Backpropagation Training Method for Neural Networks.- A Large-Update Primal-Dual Interior-Point Method for Second-Order Cone Programming.- A One-Step Smoothing Newton Method Based on a New Class of One-Parametric Nonlinear Complementarity Functions for P 0-NCP.- A Neural Network Algorithm for Solving Quadratic Programming Based on Fibonacci Method.- A Hybrid Particle Swarm Optimization Algorithm Based on Nonlinear Simplex Method and Tabu Search.- Fourier Series Chaotic Neural Networks.- Multi-objective Optimization of Grades Based on Soft Computing.- Connectivity Control Methods and Decision Algorithms Using Neural Network in Decentralized Networks.- A Quantum-Inspired Artificial Immune System for Multiobjective 0-1 Knapsack Problems.- RBF Neural Network Based on Particle Swarm Optimization.- Genetic-Based Granular Radial Basis Function Neural Network.- A Closed-Form Solution to the Problem of Averaging over the Lie Group of Special Orthogonal Matrices.- A Lower Order Discrete-Time Recurrent Neural Network for Solving High Order Quadratic Problems with Equality Constraints.- A Experimental Study on Space Search Algorithm in ANFIS-Based Fuzzy Models.- Optimized FCM-Based Radial Basis Function Neural Networks: A Comparative Analysis of LSE and WLSE Method.- Design of Information Granulation-Based Fuzzy Radial Basis Function Neural Networks Using NSGA-II.- Practical Criss-Cross Method for Linear Programming.- Calculating the Shortest Paths by Matrix Approach.- A Particle Swarm Optimization Heuristic for the Index Tacking Problem.- Structural Design of Optimized Polynomial Radial Basis Function Neural Networks.- Convergence of the Projection-Based Generalized Neural Network and the Application to Nonsmooth Optimization Problems.- Two-Dimensional Adaptive Growing CMAC Network.- A Global Inferior-Elimination Thermodynamics Selection Strategy for Evolutionary Algorithm.- Particle Swarm Optimization Based Learning Method for Process Neural Networks.- Interval Fitness Interactive Genetic Algorithms with Variational Population Size Based on Semi-supervised Learning.- Research on One-Dimensional Chaos Maps for Fuzzy Optimal Selection Neural Network.- Edited Nearest Neighbor Rule for Improving Neural Networks Classifications.- A New Algorithm for Generalized Wavelet Transform.- Neural Networks Algorithm Based on Factor Analysis.- IterativeSOMSO: An Iterative Self-organizing Map for Spatial Outlier Detection.- A Novel Method of Neural Network Optimized Design Based on Biologic Mechanism.- Research on a Novel Ant Colony Optimization Algorithm.- A Sparse Infrastructure of Wavelet Network for Nonparametric Regression.- Information Distances over Clusters.- Learning and Inference.- Regression Transfer Learning Based on Principal Curve.- Semivariance Criteria for Quantifying the Choice among Uncertain Outcomes.- Enhanced Extreme Learning Machine with Modified Gram-Schmidt Algorithm.- Solving Large N-Bit Parity Problems with the Evolutionary ANN Ensemble.- Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries.- Local Bayesian Based Rejection Method for HSC Ensemble.- Orthogonal Least Squares Based on Singular Value Decomposition for Spare Basis Selection.- Spectral Clustering on Manifolds with Statistical and Geometrical Similarity.- A Supervised Fuzzy Adaptive Resonance Theory with Distributed Weight Update.- A Hybrid Neural Network Model Based Reinforcement Learning Agent.- A Multi-view Regularization Method for Semi-supervised Learning.- Multi-reservoir Echo State Network with Sparse Bayesian Learning.- Leave-One-Out Cross-Validation Based Model Selection for Manifold Regularization.- Probability Density Estimation Based on Nonparametric Local Kernel Regression.- A Framework of Decision Making Based on Maximal Supported Sets.- Neurodynamics.- Dynamics of Competitive Neural Networks with Inverse Lipschitz Neuron Activations.- Stability and Hopf Bifurcation of a BAM Neural Network with Delayed Self-feedback.- Stability Analysis of Recurrent Neural Networks with Distributed Delays Satisfying Lebesgue-Stieljies Measures.- Stability of Genetic Regulatory Networks with Multiple Delays via a New Functional.- The Impulsive Control of the Projective Synchronization in the Drive-Response Dynamical Networks with Coupling Delay.- Novel LMI Stability Criteria for Interval Hopfield Neural Networks with Time Delays.- Memetic Evolutionary Learning for Local Unit Networks.- Synchronization for a Class of Uncertain Chaotic Cellular Neural Networks with Time-Varying Delay.- Global Exponential Stability of Equilibrium Point of Hopfield Neural Network with Delay.- Stability of Impulsive Cohen-Grossberg Neural Networks with Delays.- P-Moment Asymptotic Behavior of Nonautonomous Stochastic Differential Equation with Delay.- Exponential Stability of the Neural Networks with Discrete and Distributed Time-Varying Delays.- Mean Square Stability in the Numerical Simulation of Stochastic Delayed Hopfield Neural Networks with Markovian Switching.- The Existence of Anti-periodic Solutions for High-Order Cohen-Grossberg Neural Networks.- Global Exponential Stability of BAM Type Cohen-Grossberg Neural Network with Delays on Time Scales.- Multistability of Delayed Neural Networks with Discontinuous Activations.- Finite-Time Boundedness Analysis of Uncertain CGNNs with Multiple Delays.- Dissipativity Analysis of Stochastic Neural Networks with Time-Varying Delays.- Multistability Analysis: High-Order Networks Do Not Imply Greater Storage Capacity Than First-Order Ones.- Properties of Periodic Solutions for Common Logistic Model with Discrete and Distributed Delay.- New Results of Globally Exponentially Attractive Set and Synchronization Controlling of the Qi Chaotic System.- Stability and Attractive Basin of Delayed Cohen-Grossberg Neural Networks.- Exponential Stability Analysis for Discrete-Time Stochastic BAM Neural Networks with Time-Varying Delays.- Invariant and Globally Exponentially Attractive Sets of Separated Variables Systems with Time-Varying Delays.- Delay-Dependent Stability of Nonlinear Uncertain Stochastic Systems with Time-Varying Delays.- Stability Analysis of Fuzzy Cohen-Grossberg Neural Networks with Distributed Delays and Reaction-Diffusion Terms.- Global Exponential Robust Stability of Delayed Hopfield Neural Networks with Reaction-Diffusion Terms.- Stability and Bifurcation of a Three-Dimension Discrete Neural Network Model with Delay.- Globally Exponential Stability of a Class of Neural Networks with Impulses and Variable Delays.- Discrete Time Nonlinear Identification via Recurrent High Order Neural Networks for a Three Phase Induction Motor.- Stability Analysis for Stochastic BAM Neural Networks with Distributed Time Delays.- Dissipativity in Mean Square of Non-autonomous Impulsive Stochastic Neural Networks with Delays.- Stability Analysis of Discrete Hopfield Neural Networks Combined with Small Ones.


Titel: Advances in Neural Networks -- ISNN 2010
Untertitel: 7th International Symposium on Neural Networks, ISNN 2010, Shanghai, China, June 6-9, 2010, Proceedings, Part I
EAN: 9783642132773
ISBN: 3642132774
Format: Kartonierter Einband
Herausgeber: Springer Berlin Heidelberg
Genre: Informatik
Anzahl Seiten: 792
Gewicht: 1177g
Größe: H235mm x B155mm x T42mm
Jahr: 2010
Auflage: 2010

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