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Advances in Neural Networks - ISNN 2005

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The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Netw... Weiterlesen
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The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Networks, ISNN 2005, held in Chongqing, China in May/June 2005.

The 483 revised papers presented were carefully reviewed and selected from 1.425 submissions. The papers are organized in topical sections on theoretical analysis, model design, learning methods, optimization methods, kernel methods, component analysis, pattern analysis, systems modeling, signal processing, image processing, financial analysis, control systems, robotic systems, telecommunication networks, incidence detection, fault diagnosis, power systems, biomedical applications, industrial applications, and other applications.

Includes supplementary material: sn.pub/extras

Theoretical Analysis.- Population Coding, Bayesian Inference and Information Geometry.- One-Bit-Matching ICA Theorem, Convex-Concave Programming, and Combinatorial Optimization.- Dynamic Models for Intention (Goal-Directedness) Are Required by Truly Intelligent Robots.- Differences and Commonalities Between Connectionism and Symbolicism.- Pointwise Approximation for Neural Networks.- On the Universal Approximation Theorem of Fuzzy Neural Networks with Random Membership Function Parameters.- A Review: Relationship Between Response Properties of Visual Neurons and Advances in Nonlinear Approximation Theory.- Image Representation in Visual Cortex and High Nonlinear Approximation.- Generalization and Property Analysis of GENET.- On Stochastic Neutral Neural Networks.- Eigenanalysis of CMAC Neural Network.- A New Definition of Sensitivity for RBFNN and Its Applications to Feature Reduction.- Complexity of Error Hypersurfaces in Multilayer Perceptrons with General Multi-input and Multi-output Architecture.- Nonlinear Dynamical Analysis on Coupled Modified Fitzhugh-Nagumo Neuron Model.- Stability of Nonautonomous Recurrent Neural Networks with Time-Varying Delays.- Global Exponential Stability of Non-autonomous Neural Networks with Variable Delay.- A Generalized LMI-Based Approach to the Global Exponential Stability of Recurrent Neural Networks with Delay.- A Further Result for Exponential Stability of Neural Networks with Time-Varying Delays.- Improved Results for Exponential Stability of Neural Networks with Time-Varying Delays.- Global Exponential Stability of Recurrent Neural Networks with Infinite Time-Varying Delays and Reaction-Diffusion Terms.- Exponential Stability Analysis of Neural Networks with Multiple Time Delays.- Exponential Stability of Cohen-Grossberg Neural Networks with Delays.- Global Exponential Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays and Continuously Distributed Delays.- Exponential Stability of Stochastic Cohen-Grossberg Neural Networks with Time-Varying Delays.- Exponential Stability of Fuzzy Cellular Neural Networks with Unbounded Delay.- Global Exponential Stability of Reaction-Diffusion Hopfield Neural Networks with Distributed Delays.- Global Exponential Stability of Delayed Impulsive Hopfield Type Neural Networks.- Global Exponential Stability of Hopfield Neural Networks with Impulsive Effects.- Global Exponential Stability of Discrete Time Hopfield Neural Networks with Delays.- Stability Analysis of Uncertain Neural Networks with Linear and Nonlinear Time Delays.- Robust Stability for Delayed Neural Networks with Nonlinear Perturbation.- Robust Stability Analysis of a Class of Hopfield Neural Networks with Multiple Delays.- Robust Stability of Interval Delayed Neural Networks.- Impulsive Robust Control of Interval Hopfield Neural Networks.- Global Attractivity of Cohen-Grossberg Model with Delays.- High-Order Hopfield Neural Networks.- Stability Analysis of Second Order Hopfield Neural Networks with Time Delays.- Convergence Analysis of Genetic Regulatory Networks Based on Nonlinear Measures.- Stability Conditions for Discrete Neural Networks in Partial Simultaneous Updating Mode.- Dynamic Behavior Analysis of Discrete Neural Networks with Delay.- Existence and Stability of Periodic Solution in a Class of Impulsive Neural Networks.- Globally Attractive Periodic Solutions of Continuous-Time Neural Networks and Their Discrete-Time Counterparts.- Globally Stable Periodic State of Delayed Cohen-Grossberg Neural Networks.- Globally Attractive Periodic State of Discrete-Time Cellular Neural Networks with Time-Varying Delays.- An Analysis for Periodic Solutions of High-Order BAM Neural Networks with Delays.- Periodic Oscillation and Exponential Stability of a Class of Competitive Neural Networks.- Synchronous Behaviors of Two Coupled Neurons.- Adaptive Synchronization of Delayed Neural Networks Based on Parameters Identification.- Strength and Direction of Phase Synchronization of Neural Networks.- Hopf Bifurcation in a Single Inertial Neuron Model: A Frequency Domain Approach.- Hopf Bifurcation in a Single Inertial Neuron Model with a Discrete Delay.- Stability and Bifurcation of a Neuron Model with Delay-Dependent Parameters.- Stability and Chaos of a Neural Network with Uncertain Time Delays.- Chaotic Synchronization of Delayed Neural Networks.- Chaos Synchronization for Bi-directional Coupled Two-Neuron Systems with Discrete Delays.- Complex Dynamics in a Simple Hopfield-Type Neural Network.- Adaptive Chaotic Controlling Method of a Chaotic Neural Network Model.- Model Design.- Modeling Cortex Network: A Spatio-temporal Population Approach.- A Special Kind of Neural Networks: Continuous Piecewise Linear Functions.- A Novel Dynamic Structural Neural Network with Neuron-Regeneration and Neuron-Degeneration Mechanisms.- A New Adaptive Ridgelet Neural Network.- Designing Neural Networks Using Hybrid Particle Swarm Optimization.- A New Strategy for Designing Bidirectional Associative Memories.- Genetically Optimized Hybrid Fuzzy Neural Networks Based on TSK Fuzzy Rules and Polynomial Neurons.- Genetically Optimized Self-organizing Fuzzy Polynomial Neural Networks Based on Information Granulation.- Identification of ANFIS-Based Fuzzy Systems with the Aid of Genetic Optimization and Information Granulation.- Design of Rule-Based Neurofuzzy Networks by Means of Genetic Fuzzy Set-Based Granulation.- Design of Genetic Fuzzy Set-Based Polynomial Neural Networks with the Aid of Information Granulation.- A Novel Self-organizing Neural Fuzzy Network for Automatic Generation of Fuzzy Inference Systems.- Constructive Fuzzy Neural Networks and Its Application.- A Novel CNN Template Design Method Based on GIM.- A Novel Generalized Congruence Neural Networks.- A SOM Based Model Combination Strategy.- Typical Sample Selection and Redundancy Reduction for Min-Max Modular Network with GZC Function.- Parallel Feedforward Process Neural Network with Time-Varying Input and Output Functions.- A Novel Solid Neuron-Network Chip Based on Both Biological and Artificial Neural Network Theories.- Associative Memory Using Nonlinear Line Attractor Network for Multi-valued Pattern Association.- Associative Chaotic Neural Network via Exponential Decay Spatio-temporal Effect.- On a Chaotic Neural Network with Decaying Chaotic Noise.- Extension Neural Network-Type 3.- Pulsed Para-neural Networks (PPNN) Based on MEXORs and Counters.- Using Ensemble Information in Swarming Artificial Neural Networks.- Negatively Correlated Neural Network Ensemble with Multi-population Particle Swarm Optimization.- Wrapper Approach for Learning Neural Network Ensemble by Feature Selection.- Constructive Ensemble of RBF Neural Networks and Its Application to Earthquake Prediction.- Learning Methods.- The Bounds on the Rate of Uniform Convergence for Learning Machine.- Supervised Learning on Local Tangent Space.- Study Markov Neural Network by Stochastic Graph.- An Efficient Recursive Total Least Squares Algorithm for Training Multilayer Feedforward Neural Networks.- A Robust Learning Algorithm for Feedforward Neural Networks with Adaptive Spline Activation Function.- A New Modified Hybrid Learning Algorithm for Feedforward Neural Networks.- Robust Recursive TLS (Total Least Square) Method Using Regularized UDU Decomposed for FNN (Feedforward Neural Network) Training.- An Improved Backpropagation Algorithm Using Absolute Error Function.- An Improved Relative Criterion Using BP Algorithm.- Solving Hard Local Minima Problems Using Basin Cells for Multilayer Perceptron Training.- Enhanced Fuzzy Single Layer Perceptron.- A New Training Algorithm for a Fuzzy Perceptron and Its Convergence.- Stochastic Fuzzy Neural Network and Its Robust Parameter Learning Algorithm.- Applying Neural Network to Reinforcement Learning in Continuous Spaces.- Multiagent Reinforcement Learning Algorithm Using Temporal Difference Error.- A Foremost-Policy Reinforcement Learning Based ART2 Neural Network and Its Learning Algorithm.- A Reinforcement Learning Based Radial-Bassis Function Network Control System.- Structure Pruning Strategies for Min-Max Modular Network.- Sequential Bayesian Learning for Modular Neural Networks.- A Modified Genetic Algorithm for Fast Training Neural Networks.- Immunity Clonal Synergetic Learning of Unbalanced Attention Parameters in Synergetic Network.- Optimizing Weights of Neural Network Using an Adaptive Tabu Search Approach.- Semi-supervised Learning for Image Retrieval Using Support Vector Machines.- A Simple Rule Extraction Method Using a Compact RBF Neural Network.- Automatic Fuzzy Rule Extraction Based on Fuzzy Neural Network.- Optimization Methods.- Neural Networks for Nonconvex Nonlinear Programming Problems: A Switching Control Approach.- Deterministic Global Optimization with a Neighbourhood Determination Algorithm Based on Neural Networks.- A Neural Network Methodology of Quadratic Optimization with Quadratic Equality Constraints.- A Hopfiled Neural Network for Nonlinear Constrained Optimization Problems Based on Penalty Function.- A Neural Network Algorithm for Second-Order Conic Programming.- Application of Neural Network to Interactive Physical Programming.- Application of the Winner Takes All Principle in Wang's Recurrent Neural Network for the Assignment Problem.- Theoretical Analysis and Parameter Setting of Hopfield Neural Networks.- Solving Optimization Problems Based on Chaotic Neural Network with Hysteretic Activation Function.- An Improved Transiently Chaotic Neural Network for Solving the K-Coloring Problem.- A Sweep-Based TCNN Algorithm for Capacity Vehicle Routing Problem.- Transient Chaotic Discrete Neural Network for Flexible Job-Shop Scheduling.- Integration of Artificial Neural Networks and Genetic Algorithm for Job-Shop Scheduling Problem.- An Effective Algorithm Based on GENET Neural Network Model for Job Shop Scheduling with Release Dates and Due Dates.- Fuzzy Due Dates Job Shop Scheduling Problem Based on Neural Network.- Heuristic Combined Artificial Neural Networks to Schedule Hybrid Flow Shop with Sequence Dependent Setup Times.- A Neural Network Based Heuristic for Resource-Constrained Project Scheduling.- Functional-Link Net Based Multiobjective Fuzzy Optimization.- Optimizing the Distributed Network Monitoring Model with Bounded Bandwidth and Delay Constraints by Neural Networks.- Stochastic Nash Equilibrium with a Numerical Solution Method.- Kernel Methods.- Generalized Foley-Sammon Transform with Kernels.- Sparse Kernel Fisher Discriminant Analysis.- Scaling the Kernel Function to Improve Performance of the Support Vector Machine.- Online Support Vector Machines with Vectors Sieving Method.- Least Squares Support Vector Machine Based on Continuous Wavelet Kernel.- Multiple Parameter Selection for LS-SVM Using Smooth Leave-One-Out Error.- Trajectory-Based Support Vector Multicategory Classifier.- Multi-category Classification by Least Squares Support Vector Regression.- Twi-Map Support Vector Machine for Multi-classification Problems.- Fuzzy Multi-class SVM Classifier Based on Optimal Directed Acyclic Graph Using in Similar Handwritten Chinese Characters Recognition.- A Hierarchical and Parallel Method for Training Support Vector Machines.- Task Decomposition Using Geometric Relation for Min-Max Modular SVMs.- A Novel Ridgelet Kernel Regression Method.- Designing Nonlinear Classifiers Through Minimizing VC Dimension Bound.- A Cascaded Mixture SVM Classifier for Object Detection.- Radar High Range Resolution Profiles Feature Extraction Based on Kernel PCA and Kernel ICA.- Controlling Chaotic Systems via Support Vector Machines Without Analytical Model.- Support Vector Regression for Software Reliability Growth Modeling and Prediction.- SVM-Based Semantic Text Categorization for Large Scale Web Information Organization.- Fuzzy Support Vector Machine and Its Application to Mechanical Condition Monitoring.- Component Analysis.- Guided GA-ICA Algorithms.- A Cascaded Ensemble Learning for Independent Component Analysis.- A Step by Step Optimization Approach to Independent Component Analysis.- Self-adaptive FastICA Based on Generalized Gaussian Model.- An Efficient Independent Component Analysis Algorithm for Sub-Gaussian Sources.- ICA and Committee Machine-Based Algorithm for Cursor Control in a BCI System.- Fast Independent Component Analysis for Face Feature Extraction.- Affine Invariant Descriptors for Color Images Based on Independent Component Analysis.- A New Image Protection and Authentication Technique Based on ICA.- Locally Spatiotemporal Saliency Representation: The Role of Independent Component Analysis.- A Multistage Decomposition Approach for Adaptive Principal Component Analysis.- A New Kalman Filtering Algorithm for Nonlinear Principal Component Analysis.- An Improvement on PCA Algorithm for Face Recognition.- A Modified PCA Neural Network to Blind Estimation of the PN Sequence in Lower SNR DS-SS Signals.- A Modified MCA EXIN Algorithm and Its Convergence Analysis.- Robust Beamforming by a Globally Convergent MCA Neural Network.


Titel: Advances in Neural Networks - ISNN 2005
Untertitel: Second International Symposium on Neural Networks, Chongqing, China, May 30 - June 1, 2005, Proceedings, Part I
EAN: 9783540259121
ISBN: 978-3-540-25912-1
Format: Kartonierter Einband
Herausgeber: Springer, Berlin
Genre: Informatik
Anzahl Seiten: 1055
Gewicht: 1639g
Größe: H62mm x B234mm x T152mm
Jahr: 2005
Untertitel: Englisch
Auflage: 2005. 2005

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