Advances in Neural Networks - Isnn 2004: International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part I (Paperback, 2004)

Theoretical Analysis.- Approximation Bounds by Neural Networks in L ? p [-4pt].- Geometric Interpretation of Nonlinear Approximation Capability for Feedforward Neural Networks.- Mutual Information and Topology 1: Asymmetric Neural Network.- Mutual Information and Topology 2: Symmetric Network.- Simplified PCNN and Its Periodic Solutions.- On Robust Periodicity of Delayed Dynamical Systems with Time-Varying Parameters.- Delay-Dependent Criteria for Global Stability of Delayed Neural Network System.- Stability Analysis of Uncertain Neural Networks with Delay.- A New Method for Robust Stability Analysis of a Class of Recurrent Neural Networks with Time Delays.- Criteria for Stability in Neural Network Models with Iterative Maps.- Exponential Stability Analysis for Neural Network with Parameter Fluctuations.- Local Stability and Bifurcation in a Model of Delayed Neural Network.- On the Asymptotic Stability of Non-autonomous Delayed Neural Networks.- Global Exponential Stability of Cohen-Grossberg Neural Networks with Multiple Time-Varying Delays.- Stability of Stochastic Cohen-Grossberg Neural Networks.- A Novel Approach to Exponential Stability Analysis of Cohen-Grossberg Neural Networks.- Analysis for Global Robust Stability of Cohen-Grossberg Neural Networks with Multiple Delays.- On Robust Stability of BAM Neural Networks with Constant Delays.- Absolutely Exponential Stability of BAM Neural Networks with Distributed Delays.- Stability Analysis of Discrete-Time Cellular Neural Networks.- Novel Exponential Stability Criteria for Fuzzy Cellular Neural Networks with Time-Varying Delay.- Stability of Discrete Hopfield Networks with Delay in Serial Mode.- Further Results for an Estimation of Upperbound of Delays for Delayed Neural Networks.- Synchronization in Two Uncoupled Chaotic Neurons.- Robust Synchronization of Coupled Delayed Recurrent Neural Networks.- Learning and Optimization.- Self-Optimizing Neural Networks.- Genetically Optimized Self-Organizing Neural Networks Based on PNs and FPNs.- A New Approach to Self-Organizing Hybrid Fuzzy Polynomial Neural Networks: Synthesis of Computational Intelligence Technologies.- On Soft Learning Vector Quantization Based on Reformulation.- A New Approach to Self-Organizing Polynomial Neural Networks by Means of Genetic Algorithms.- Fuzzy-Kernel Learning Vector Quantization.- Genetic Generation of High-Degree-of-Freedom Feed-Forward Neural Networks.- Self-Organizing Feature Map Based Data Mining.- Diffusion and Growing Self-Organizing Map: A Nitric Oxide Based Neural Model.- A New Adaptive Self-Organizing Map.- Evolving Flexible Neural Networks Using Ant Programming and PSO Algorithm.- Surrogating Neurons in an Associative Chaotic Neural Network.- Ensembles of RBFs Trained by Gradient Descent.- Gradient Descent Training of Radial Basis Functions.- Recent Developments on Convergence of Online Gradient Methods for Neural Network Training.- A Regularized Line Search Tunneling for Efficient Neural Network Learning.- Transductive Learning Machine Based on the Affinity-Rule for Semi-supervised Problems and Its Algorithm.- A Learning Algorithm with Gaussian Regularizer for Kernel Neuron.- An Effective Learning Algorithm of Synergetic Neural Network.- Sparse Bayesian Learning Based on an Efficient Subset Selection.- A Novel Fuzzy Neural Network with Fast Training and Accurate Generalization.- Tuning Neuro-Fuzzy Function Approximator by Tabu Search.- Finite Convergence of MRI Neural Network for Linearly Separable Training Patterns.- A Rapid Two-Step Learning Algorithm for Spline Activation Function Neural Networks with the Application on Biped Gait Recognition.- An Online Feature Learning Algorithm Using HCI-Based Reinforcement Learning.- Optimizing the Weights of Neural Networks Based on Antibody Clonal Simulated Annealing Algorithm.- Backpropagation Analysis of the Limited Precision on High-Order Function Neural Networks.- LMS Adaptive Notch Filter Design Based on Immune Algorithm.- Training R