Advances in Neural Networks - ISNN 2006 /1

Robust Stability of Markovian Jump Nonlinear Uncertain Neural Networks with Wiener Process.- Stochastic Robust Stability Analysis for Markovian Jump Discrete-Time Delayed Neural Networks with Multiplicative Nonlinear Perturbations.- Global Robust Stability of General Recurrent Neural Networks with Time-Varying Delays.- Robust Periodicity in Recurrent Neural Network with Time Delays and Impulses.- Global Asymptotical Stability of Cohen-Grossberg Neural Networks with Time-Varying and Distributed Delays.- LMI Approach to Robust Stability Analysis of Cohen-Grossberg Neural Networks with Multiple Delays.- Existence and Global Stability Analysis of Almost Periodic Solutions for Cohen-Grossberg Neural Networks.- A New Sufficient Condition on the Complete Stability of a Class Cellular Neural Networks.- Stability Analysis of Reaction-Diffusion Recurrent Cellular Neural Networks with Variable Time Delays.- Exponential Stability of Delayed Stochastic Cellular Neural Networks.- Global Exponential Stability of Cellular Neural Networks with Time-Varying Delays and Impulses.- Global Exponential Stability of Fuzzy Cellular Neural Networks with Variable Delays.- Stability of Fuzzy Cellular Neural Networks with Impulses.- Absolute Stability of Hopfield Neural Network.- Robust Stability Analysis of Uncertain Hopfield Neural Networks with Markov Switching.- Asymptotic Stability of Second-Order Discrete-Time Hopfield Neural Networks with Variable Delays.- Convergence Analysis of Discrete Delayed Hopfield Neural Networks.- An LMI-Based Approach to the Global Stability of Bidirectional Associative Memory Neural Networks with Variable Delay.- Existence of Periodic Solution of BAM Neural Network with Delay and Impulse.- On Control of Hopf Bifurcation in BAM Neural Network with Delayed Self-feedback.- Convergence and Periodicity of Solutions for a Class of Discrete-Time Recurrent Neural Network with Two Neurons.- Existence and Global Attractability of Almost Periodic Solution for Competitive Neural Networks with Time-Varying Delays and Different Time Scales.- Global Synchronization of Impulsive Coupled Delayed Neural Networks.- Synchronization of a Class of Coupled Discrete Recurrent Neural Networks with Time Delay.- Chaos and Bifurcation in a New Class of Simple Hopfield Neural Network.- Synchronization of Chaotic System with the Perturbation Via Orthogonal Function Neural Network.- Numerical Analysis of a Chaotic Delay Recurrent Neural Network with Four Neurons.- Autapse Modulated Bursting.- Neurodynamic Optimization.- A Neural Network Model for Non-smooth Optimization over a Compact Convex Subset.- Differential Inclusions-Based Neural Networks for Nonsmooth Convex Optimization on a Closed Convex Subset.- A Recurrent Neural Network for Linear Fractional Programming with Bound Constraints.- A Delayed Lagrangian Network for Solving Quadratic Programming Problems with Equality Constraints.- Wavelet Chaotic Neural Networks and Their Application to Optimization Problems.- A New Optimization Algorithm Based on Ant Colony System with Density Control Strategy.- A New Neural Network Approach to the Traveling Salesman Problem.- Dynamical System for Computing Largest Generalized Eigenvalue.- A Concise Functional Neural Network for Computing the Extremum Eigenpairs of Real Symmetric Matrices.- Learning Algorithms.- A Novel Stochastic Learning Rule for Neural Networks.- Learning with Single Quadratic Integrate-and-Fire Neuron.- Manifold Learning of Vector Fields.- Similarity Measure for Vector Field Learning.- The Mahalanobis Distance Based Rival Penalized Competitive Learning Algorithm.- Dynamic Competitive Learning.- Hyperbolic Quotient Feature Map for Competitive Learning Neural Networks.- A Gradient Entropy Regularized Likelihood Learning Algorithm on Gaussian Mixture with Automatic Model Selection.- Self-organizing Neural Architecture for Reinforcement Learning.- On the Efficient Implementation Biologic Reinforcement Learning Using Eligibility Traces.- Combining Label Information and Neighborhood Graph for Semi-supervised Learning.- A Cerebellar Feedback Error Learning Scheme Based on Kalman Estimator for Tracing in Dynamic System.- An Optimal Iterative Learning Scheme for Dynamic Neural Network Modelling.- Delayed Learning on Internal Memory Network and Organizing Internal States.- A Novel Learning Algorithm for Feedforward Neural Networks.- On H??? Filtering in Feedforward Neural Networks Training and Pruning.- A Node Pruning Algorithm Based on Optimal Brain Surgeon for Feedforward Neural Networks.- A Fast Learning Algorithm Based on Layered Hessian Approximations and the Pseudoinverse.- A Modular Reduction Method for k-NN Algorithm with Self-recombination Learning.- Selective Neural Network Ensemble Based on Clustering.- An Individual Adaptive Gain Parameter Backpropagation Algorithm for Complex-Valued Neural Networks.- Training Cellular Neural Networks with Stable Learning Algorithm.- A New Stochastic PSO Technique for Neural Network Training.- A Multi-population Cooperative Particle Swarm Optimizer for Neural Network Training.- Training RBF Neural Network with Hybrid Particle Swarm Optimization.- Robust Learning by Self-organization of Nonlinear Lines of Attractions.- Improved Learning Algorithm Based on Generalized SOM for Dynamic Non-linear System.- Q-Learning with FCMAC in Multi-agent Cooperation.- Q Learning Based on Self-organizing Fuzzy Radial Basis Function Network.- A Fuzzy Neural Networks with Structure Learning.- Reinforcement Learning-Based Tuning Algorithm Applied to Fuzzy Identification.- A New Learning Algorithm for Function Approximation Incorporating A Priori Information into Extreme Learning Machine.- Robust Recursive Complex Extreme Learning Machine Algorithm for Finite Numerical Precision.- Evolutionary Extreme Learning Machine - Based on Particle Swarm Optimization.- A Gradient-Based ELM Algorithm in Regressing Multi-variable Functions.- A New Genetic Approach to Structure Learning of Bayesian Networks.- Model Design.- Research on Multi-Degree-of-Freedom Neurons with Weighted Graphs.- Output PDF Shaping of Singular Weights System: Monotonical Performance Design.- Stochastic Time-Varying Competitive Neural Network Systems.- Heterogeneous Centroid Neural Networks.- Building Multi-layer Small World Neural Network.- Growing Hierarchical Principal Components Analysis Self-Organizing Map.- Hybrid Neural Network Model Based on Multi-layer Perceptron and Adaptive Resonance Theory.- Evolving Neural Networks Using the Hybrid of Ant Colony Optimization and BP Algorithms.- A Genetic Algorithm with Modified Tournament Selection and Efficient Deterministic Mutation for Evolving Neural Network.- A Neural Network Structure Evolution Algorithm Based on e, m Projections and Model Selection Criterion.- A Parallel Coevolutionary Immune Neural Network and Its Application to Signal Simulation.- A Novel Elliptical Basis Function Neural Networks Optimized by Particle Swarm Optimization.- Fuzzy Neural Network Optimization by a Particle Swarm Optimization Algorithm.- Fuzzy Rule Extraction Using Robust Particle Swarm Optimization.- A New Design Methodology of Fuzzy Set-Based Polynomial Neural Networks with Symbolic Gene Type Genetic Algorithms.- Design of Fuzzy Polynomial Neural Networks with the Aid of Genetic Fuzzy Granulation and Its Application to Multi-variable Process System.- A Novel Self-Organizing Fuzzy Polynomial Neural Networks with Evolutionary FPNs: Design and Analysis.- Design of Fuzzy Neural Networks Based on Genetic Fuzzy Granulation and Regression Polynomial Fuzzy Inference.- A New Fuzzy ART Neural Network Based on Dual Competition and Resonance Technique.- Simulated Annealing Based Learning Approach for the Design of Cascade Architectures of Fuzzy Neural Networks.- A New Fuzzy Identification Method Based on Adaptive Critic Designs.- Impacts of Perturbations of Training Patterns on Two Fuzzy Associative Memories Based on T-Norms.- Alpha-Beta Associative Memories for Gray Level Patterns.- Associative Memories Based on Discrete-Time Cellular Neural Networks with One-Dimensional Space-Invariant Templates.- Autonomous and Deterministic Probabilistic Neural Network Using Global k-Means.- Selecting Variables for Neural Network Committees.- An Adaptive Network Topology for Classification.- A Quantitative Comparison of Different MLP Activation Functions in Classification.- Estimating the Number of Hidden Neurons in a Feedforward Network Using the Singular Value Decomposition.- Neuron Selection for RBF Neural Network Classifier Based on Multiple Granularities Immune Network.- Hierarchical Radial Basis Function Neural Networks for Classification Problems.- Biased Wavelet Neural Network and Its Application to Streamflow Forecast.- A Goal Programming Based Approach for Hidden Targets in Layer-by-Layer Algorithm of Multilayer Perceptron Classifiers.- SLIT: Designing Complexity Penalty for Classification and Regression Trees Using the SRM Principle.- Flexible Neural Tree for Pattern Recognition.- A Novel Model of Artificial Immune Network and Simulations on Its Dynamics.- Kernel Methods.- A Kernel Optimization Method Based on the Localized Kernel Fisher Criterion.- Genetic Granular Kernel Methods for Cyclooxygenase-2 Inhibitor Activity Comparison.- Support Vector Machines with Beta-Mixing Input Sequences.- Least Squares Support Vector Machine on Gaussian Wavelet Kernel Function Set.- A Smoothing Multiple Support Vector Machine Model.- Fuzzy Support Vector Machines Based on Spherical Regions.- Building Support Vector Machine Alternative Using Algorithms of Computational Geometry.- Cooperative Clustering for Training SVMs.- SVMV - A Novel Algorithm for the Visualization of SVM Classification Results.- Support Vector Machines Ensemble Based on Fuzzy Integral for Classification.- An Adaptive Support Vector Machine Learning Algorithm for Large Classification Problem.- SVDD-Based Method for Fast Training of Multi-class Support Vector Classifier.- Binary Tree Support Vector Machine Based on Kernel Fisher Discriminant for Multi-classification.- A Fast and Sparse Implementation of Multiclass Kernel Perceptron Algorithm.- Mutual Conversion of Regression and Classification Based on Least Squares Support Vector Machines.- Sparse Least Squares Support Vector Machine for Function Estimation.- A Multiresolution Wavelet Kernel for Support Vector Regression.- Multi-scale Support Vector Machine for Regression Estimation.- Gradient Based Fuzzy C-Means Algorithm with a Mercer Kernel.- An Efficient Similarity-Based Validity Index for Kernel Clustering Algorithm.- Fuzzy Support Vector Clustering.- An SVM Classification Algorithm with Error Correction Ability Applied to Face Recognition.- A Boosting SVM Chain Learning for Visual Information Retrieval.- Nonlinear Estimation of Hyperspectral Mixture Pixel Proportion Based on Kernel Orthogonal Subspace Projection.- A New Proximal Support Vector Machine for Semi-supervised Classification.- Sparse Gaussian Processes Using Backward Elimination.- Comparative Study of Extreme Learning Machine and Support Vector Machine.- ICA and BSS.- Multi-level Independent Component Analysis.- An ICA Learning Algorithm Utilizing Geodesic Approach.- An Extended Online Fast-ICA Algorithm.- Gradient Algorithm for Nonnegative Independent Component Analysis.- Unified Parametric and Non-parametric ICA Algorithm for Arbitrary Sources.- A Novel Kurtosis-Dependent Parameterized Independent Component Analysis Algorithm.- Local Stability Analysis of Maximum Nongaussianity Estimation in Independent Component Analysis.- Convergence Analysis of a Discrete-Time Single-Unit Gradient ICA Algorithm.- An Novel Algorithm for Blind Source Separation with Unknown Sources Number.- Blind Source Separation Based on Generalized Variance.- Blind Source Separation with Pattern Expression NMF.- Nonlinear Blind Source Separation Using Hybrid Neural Networks.- Identification of Mixing Matrix in Blind Source Separation.- Identification of Independent Components Based on Borel Measure for Under-Determined Mixtures.- Estimation of Delays and Attenuations for Underdetermined BSS in Frequency Domain.- Application of Blind Source Separation to Five-Element Cross Array Passive Location.- Convolutive Blind Separation of Non-white Broadband Signals Based on a Double-Iteration Method.- Multichannel Blind Deconvolution Using a Novel Filter Decomposition Method.- Two-Stage Blind Deconvolution for V-BLAST OFDM System.- Data Preprocessing.- A Comparative Study on Selection of Cluster Number and Local Subspace Dimension in the Mixture PCA Models.- Adaptive Support Vector Clustering for Multi-relational Data Mining.- Robust Data Clustering in Mercer Kernel-Induced Feature Space.- Pseudo-density Estimation for Clustering with Gaussian Processes.- Clustering Analysis of Competitive Learning Network for Molecular Data.- Self-Organizing Map Clustering Analysis for Molecular Data.- A Conscientious Rival Penalized Competitive Learning Text Clustering Algorithm.- Self-Organizing-Map-Based Metamodeling for Massive Text Data Exploration.- Ensemble Learning for Keyphrases Extraction from Scientific Document.- Grid-Based Fuzzy Support Vector Data Description.- Development of the Hopfield Neural Scheme for Data Association in Multi-target Tracking.- Determine Discounting Coefficient in Data Fusion Based on Fuzzy ART Neural Network.- Scientific Data Lossless Compression Using Fast Neural Network.- HyperSurface Classifiers Ensemble for High Dimensional Data Sets.- Designing a Decompositional Rule Extraction Algorithm for Neural Networks.- Estimating Fractal Intrinsic Dimension from the Neighborhood.- Dimensionality Reduction for Evolving RBF Networks with Particle Swarms.- Improved Locally Linear Embedding Through New Distance Computing.- An Incremental Linear Discriminant Analysis Using Fixed Point Method.- A Prewhitening RLS Projection Alternated Subspace Tracking (PAST) Algorithm.- Classification with the Hybrid of Manifold Learning and Gabor Wavelet.- A Novel Input Stochastic Sensitivity Definition of Radial Basis Function Neural Networks and Its Application to Feature Selection.- Using Ensemble Feature Selection Approach in Selecting Subset with Relevant Features.- A New Method for Feature Selection.- Improved Feature Selection Algorithm Based on SVM and Correlation.- Feature Selection in Text Classification Via SVM and LSI.- Parsimonious Feature Extraction Based on Genetic Algorithms and Support Vector Machines.- Feature Extraction for Time Series Classification Using Discriminating Wavelet Coefficients.- Feature Extraction of Underground Nuclear Explosions Based on NMF and KNMF.- Hidden Markov Model Networks for Multiaspect Discriminative Features Extraction from Radar Targets.- Application of Self-organizing Feature Neural Network for Target Feature Extraction.- Divergence-Based Supervised Information Feature Compression Algorithm.