Advances in Neural Networks - ISNN 2005 Second International Symposium on Neural Networks, Chongqing, China, May 30 - June 1, 2005, Proceedings, Part I

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.

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