Advances in Neural Networks -- ISNN 2011

Name: Advances in Neural Networks -- ISNN 2011 | 8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, May 29--June 1, 2011, Proceedings Part I
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8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, May 29--June 1, 2011, Proceedings Part I

Derong Liu Huaguang Zhang Marios Polycarpou Cesare Alippi Haibo He(Herausgeber*in)

Springer (Verlag)

Erschienen am 20. Mai 2011

XXXIV, 634 Seiten

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Inhalt

Intro
Preface
Organization
Table of Contents - Part I
Computational Neuroscience and Cognitive Science
Evaluating Humans' Implicit Attitudes towards an Embodied Conversational Agent
Introduction
Hypothesis
Presenter Agent Experiment
Brief Description of Software
Results
Conclusions and Future Work
Summary
References
Robustness of Gamma-Oscillation in Networks of Excitatory and Inhibitory Neurons with Conductance-Based Synapse
Introduction
Model and Method
Result
Conclusion and Discussion
References
Probe the Potts States in the Minicolumn Dynamics
Introduction
Minicolumn Model
Layer VI
Afferent and Efferent
Dynamical Model
Results and Discussions
Potts States
Intrinsically-Bursting Neurons
Conclusions
References
Dependence of Correlated Firing on Strength of Inhibitory Feedback
Introduction
Network Model
Methods and Results
Conclusion and Discussion
References
A New Model to Simulate the Formation of Orientation Columns Map in Visual Cortex
Introduction
Material and Method
References
Study on the Synchrony Intensity Threshold of Two Uncoupled Neurons under Different Currents' Stimulation
Introduction
The Discharge Patterns of the HR Neuron Model
Study on the Synchrony Intensity Threshold of Two Uncoupled Neurons under Different Currents' Stimulation
The HR Neuron's Phase Function and the Synchronization Judge Rules
The Synchrony Intensity Threshold of Two Uncoupled Neurons under Different Currents' Stimulation
Conclusion
References
Research on Design Method of Small World Property ESN
Introduction
Problem of ESN
Design of SWESN
Generating Small World Networks
Mapping the Nodes of Small World Network to the Neurons of SWESN
Simulations
Conclusion
References
The ART2 Network Based on Memorizing-Forgetting Mechanism
Introduction
The Theory of ART2 Network
Ebbinghaus Memorizing-Forgetting Curve and Its Theory
The Working Principle of ART2 Network Which Is Introduced the Memorizing-Forgetting Mechanism and Its Description of the Algorithm
Simulation of Experiment
The Input Samples of the Network
Results of Experiment and Analysis
Conclusions
References
Application of BP Neural Networks in Prediction of the Material Dynamic Properties
Introduction
Samples Learning and Weights Adjustment in Back Propagation Method
Program Performed
Prediction of Material Dynamic Properties
Conclusion
References
Spaces Enhance Word Segmentation and Comprehension in Tacit Reading
Introduction
Experiment
Results
Discussion
References
Intelligent Semantic-Based System for Corpus Analysis through Hybrid Probabilistic Neural Networks
Introduction
The State of the Art
Description of the Method
Experimental Results
Conclusions and Perspectives
References
Decision-Making in Drosophila with Two Conflicting Cues
Introduction
The Model
The Network Architecture
The Network Dynamics
Results
The Case of a Single Cue
The Case of Conflicting Cues
Conclusions
References
Neurodynamics and Complex Systems
Time-Varying Quadratic Programming by Zhang Neural Network Equipped with a Time-Varying Design Parameter ?(t)
Introduction
Problem Formulation and Neural-Network Solvers
ZNN Model
GNN Model
Simulation Results
Conclusions
References
Local and Global Burst Synchronization in a Noisy Small-World Neuronal Network
Introduction
Neuronal Network Model
Simulation Results
Local and Global Burst Synchronization
Effect of the Shortcut-Adding Probability
Effect of the Noise
ClosingRemarks
References
H8 Synchronization Control in Nonlinear Time-Delay Complex Dynamical Network
Introduction
Problem Formulation and Preliminaries
Main Results
Asymptotically Synchronization
Exponentially Synchronization
System with Time-Varying Delays
Simulation
Conclusion
References
Anti-synchronization and Control of New Chen's Hyperchaotic Systems
Introduction
Preliminaries
Anti-synchronization of Identical Hyperchaotic System
Numerical Simulation Results
Conclusion
References
Hopf Bifurcation Control for a Single Neuron Model with Delay-Dependent Parameters via State Feedback
Introduction
Hopf Bifurcation and Hopf Bifurcation Control
Numerical Simulations
Concluding Remarks
References
Changes in Electroencephalographic Power Spectra Associated with Reproductive Status in Frog
Introduction
Materials and Methods
Animals
Surgery
Data Acquisition
Data Processing
Statistical Analyses
Results
Discussion
References
Universal Analysis Method for Stability of Recurrent Neural Networks with Different Multiple Delays
Introduction
Problem Description and Preliminaries
Main Results
Stability of Recurrent Neural Networks with Various Kinds of Multiple Delays
Conclusions
References
A Class of New Generalized AOR Method for Augmented Systems
Introduction
The Generalized AOR Method
The Convergence of GAOR Method for Augmented Systems (1.1)
Numerical Examples
References
Detecting the Topology of a Neural Network from Partially Obtained Data Using Piecewise Granger Causality
Introduction
Theory
Granger Causality
Conditional Granger Causality
Piecewise Granger Causality
Numerical Simulations
Conclusions
References
A Survey of Signal Propagation in Feedforward Neuronal Networks
Introduction
Basic Modeling Framework
Signal Propagation in Feedforward Neuronal Networks
Synfire Propagation
Firing Rate Propagation
Applications and Computations
Signal Propagation in Feedforward Neuronal Networks with Unreliable Synapses
Conclusions and Discussions
References
Stability and Convergence Analysis
Stability of Stochastic Cohen-Grossberg Neural Networks with Mixed Time Delay and Markovian Parameters
Introduction
Problem Formulation
Main Results
An Example
References
Exponential Stability of Stochastic Neural Networks with Mixed Time-Delays
Introduction
Preliminaries
Stability Results
A Two-Dimensional Example
References
Stability of Neural Networks with Both Impulses and Time-Varying Delays on Time Scale
Introduction
Problem Formulation and Preliminaries
MainResults
Example
Conclusions
References
Synchronization of Nonidentical Chaotic Neural Networks with Time-Varying Delays
Introduction
Problem Formulation and Preliminaries
MainResult
AnExample
Conclusions
References
Blow-Up for a Class of Parabolic Equations with Nonlinear Boundary Conditions
Introduction
Blow-Up Conditions
Blow-UpSet
References
Cluster Synchronization for Discrete-Time Complex Networks
Introduction
Model Description and Preliminaries
Synchronization Criterion
Numerical Example
Conclusion
References
Stability Analysis of Fourth-Order Chua's Circuit
Introduction
Definitions and Lemmas
Main Results
Example
Conclusions
References
A Phase Reduction Method for Weakly Coupled Stochastic Oscillator Systems
Introduction
Phase Reduction Method
Uncoupled Stochastic Oscillator
Weakly Coupled Stochastic Oscillators
Analysis of Synchronization
Discussion and Conclusion
References
Anti-periodic Solutions for High-Order Neural Networks with Mixed Time Delays
Introduction
Preliminaries
Main Results
Numerical Example
References
Comparisons of Single- and Multiple-Hidden-Layer Neural Networks
Introduction and Preliminaries
Construction of Networks
Network Training
Comparisons of Networks
Approximation of a Linear Function
Approximation of a Quadratic Function
Discussion
References
Stability of Cohen-Grossberg Neural Networks with Unbounded Time-Varying Delays
Introduction
Preliminaries
Stability Analysis
An Example
Conclusions
References
Thermal Effects on Phase Response Curves and Synchronization Transition
Introduction
Spiking and Synapse Models
Temperature-Dependent PRC
Temperature Modulated Synchronization Transition in Two Neurons
Type-A Synchronization Transition
Type-B Synchronization Transition
Discussion and Conclusion
References
Robust H8 Filter Design of Delayed Neural Networks
Introduction
Problem Formulation
MainResult
An Illustrated Example
Conclusion
References
On Metastability of Cellular Neural Networks with Random Perturbations
Introduction
Action Functional of CNN with Random Perturbation
Numerical Illustrations: Two-Dimensional CNN System
Conclusions
References
Fractional-Order Boundary Controller of the Anti-stable Vibration Systems
Introduction
Problem Definition
Analysis Method Using Fractional Calculus
Conclusions
References
Existence and Global Stability of Periodic Solutions of Generalized-Brain-State-in-a- Box (GBSB) Neural Models
Introduction
Existence of Periodic Solutions
Preliminaries
The Existence of Periodic Solutions
Stability of Periodic Solution
Conclusion
Neural Network-Based Dynamic Surface Control of Nonlinear Systems with Unknown Virtual Control Coefficient
Introduction
Problem Formulation
Adaptive Controller Design
Stability Analysis
Conclusion
References
Stochastic Stability Analysis of Delayed Hopfield Neural Networks with Impulse Effects
Introduction
Problem Statement and Preliminaries
Main Results
Numerical Examples
Conclusions
References
New LMI-Based Criteria for Global Robust Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays
Introduction
Model Description and Preliminaries
Main Results
Comparison and Corollary
Illustrative Example
Conclusion
Asymptotical Stability of an SEIS Epidemic Model with Latent Age Dependence and Generally Nonlinear Contact Rate
Introduction
Model Formulation
Existence of Equilibrium
The Asymptotical Stability of the Endemic Equilibrium
Conclusion
Stochastic Exponential Stability of Cohen-Grossberg Neural Networks with Markovian Jumping Parameters and Mixed Delays
Introduction
Model Description
Main Results
Example
Conclusion
References
Neural Network Models
Periodic Solutions for High-Order Cohen-Grossberg-Type BAM Neural Networks with Time-Delays
Introduction
Preliminaries
MainResults
Examples
References
Simulation and Verification of Zhang Neural Networks and Gradient Neural Networks for Time-Varying Stein Equation Solving
Introduction
Problem Formulation and Neural Solvers
Preliminaries
Neural Solver Models Description
Computer Simulation Techniques
Kronecker Product and Vectorization
Obtaining Matrix Derivatives
ZNN Right-Hand Side
Illustrative Example
Neural-State Simulation
Residual-Error Simulation
Conclusions
References
Comparison on Continuous-Time Zhang Dynamics and Newton-Raphson Iteration for Online Solution of Nonlinear Equations
Introduction
Problem Formulation and Solvers
CTZD Model
NRI Method
Computer Testing and Simulation Results
Conclusions
References
ELM-Based Time-Variant Neural Networks with Incremental Number of Output Basis Functions
Introduction
The ELM Approach for Time-Variant Neural Networks
Proposed Output Basis Functions ELM Algorithms for TV-NN
Incremental Output Basis Functions for ELM-TV
Error Minimized Output Basis Functions for ELM-TV
Simulation Results
Time-Variant MLP System Identification
Time-Variant Narendra System Identification
Conclusions
References
Invariant Set and Attractor of Discrete-Time Impulsive Recurrent Neural Networks
Introduction
Model and Preliminaries
Main Results
Illustrative Examples
Conclusions
References
Optimal Control for Boiler Combustion System Based on Iterative Heuristic Dynamic Programming
Introduction
Adaptive Dynamic Programming (ADP)
Dynamic Programming
Adaptive Dynamic Programming
The Iterative HDP Algorithm
Building the Neural Network Model of the Boiler Combustion
Neural Network Model of the Boiler Combustion
Model Testing and Results Analysis of Generalization
Neural Network Implementation of Iteration HDP
The Model Network
The Critic Network
The Action Network
Improvement of the Training Strategy
Improvement of Utility Function
Simulation and Testing
Conclusion
References
Power System Load Forecasting Based on EEMD and ANN
Introduction
EMD and EEMD
EMD Theory
EEMD Theory
Load Forecasting Model Based on EEMD and ANN
Overview for Neural Network
Forecasting Model
Simulation of Load Forecasting
Conclusions
References
Analog Circuit Fault Diagnosis with Echo State Networks Based on Corresponding Clusters
Introduction
Introduction of Analog Circuit Fault Diagnosis
ESNs Based on Corresponding Clusters
Introduction of Echo State Networks
The Proposed Method
Training of ESNs
Experiments and Discussions
Conclusions
References
Anti Boundary Effect Wavelet Decomposition Echo State Networks
Introduction
ABE-WESNs Model
The Structure of ABE-WESNs Model
Wavelet Decomposition and Single-Branch Reconstruction
Dealing with Boundary Effect
ESN Model
Weight Factor
Experiments
Experiments Setup
Prediction of Time Series Defined on ESTSP 2008
Prediction of the Mobile Traffic Time Series
Conclusion
References
Research on Water Level Optimal Control of Boiler Drum Based on Dual Heuristic Dynamic Programming
Introduction
Adaptive Dynamic Programming (ADP)
Dynamic Programming [6]
Adaptive Dynamic Programming
Building the Neural Network Model of the Boiler Drum
The Analysis of Drum System
Building the Model of Drum System
Model Testing and Results Analysis of Generalization Ability
Designing the Neural Network Controller Based on DHP Algorithm [10]
Training the Critic Network of DHP
Training the Model Network of DHP
Training the Action Network of DHP
Simulation and Testing
Conclusion
References
Fuzzy Clustering-Based Polynomial Radial Basis Function Neural Networks (p-RBF NNs) Classifier Designed with Particle Swarm Optimization
Introduction
Fuzzy Clustering-Based p-RBF Neural Networks
The Learning Method of Fuzzy C-Means in Hidden Layer
The Learning Method of Fuzzy C-Means in Hidden Layer
The Learning Method of WLSE
Optimization Process of Fuzzy Clustering-Based p-RBF NNs
Experimental Results
Synthetic Datasets
Machine Learning Dataset
Concluding Remarks
References
Application of RBF Neural Network and Nonlinear Particle Filter in the Synthetic Ammonia Decarbornization
Introduction
Nonlinear Particle Filter
Improved RBF Neural Network
RBF Neural Network Model
Improvement of RBF Neural Network
Weights of RBF Neural Network Is Optimized by the Nonlinear Particle Filter Algorithm
Application in the Synthetic Ammonia Decarburization
Simulation and Analysis
Conclusion
References
Elman-Style Process Neural Network with Application to Aircraft Engine Health Condition Monitoring
Introduction
Process Neuron Model
Elman-Style Process Neural Network Model
Learning Algorithm
Basic Learning Algorithm
Learning Algorithm Based on Orthogonal Basis Function
Application Test
Conclusion
References
A Novel Spatial Architecture Artificial Neural Network Based on Multilayer Feedforward Network with Mutual Inhibition among Hidden Units
Introduction
Definition of Spatial Artificial Neural Network
Mathematic Model of SANN
Review of Lateral Inhibition
Mathematic Model of SANN
Learning Algorithm
Numerical Experimental
Classification Capability (XOR Problem)
Approximation Capability
Conclusion and Discussion
References
sEMG Signal Classification for the Motion Pattern of Intelligent Bionic Artificial Limb
Introduction
Key Problems of sEMG Signal Classification and Solutions
Recognition Rate
Algorithm Complexity
Robustness
Real-Time Characteristic
Conclusion and Prospection
References
Dynamic Construction of Multilayer Neural Networks for Classification
Introduction
Y/N Classifier
Construction of a Y/N Neural Network
Learning in a Y/N Neural Network
Conclusions
References
Existence of Periodic Solutions for Cohen-Grossberg Neural Networks with Time-Varying Delays and Impulses
Introduction
Preliminaries
Existence of Periodic Solution
References
Telecommunications Data Forecasting Based on a Dynamic Neuro-fuzzy Network
Introduction
Statistical Forecasting Methods
Dynamic Neurofuzzy Network (DyNF-Net)
The Training Algorithm
Simulation Results
References
Evolutionary Learning of Regularization Networks with Multi-kernel Units
Introduction
Regularization Networks
Composite and Product Kernel Functions
Genetic Parameter Search
Encoding
Operators
Fitness
Experiments
Conclusion
References
Solving the Assignment Problem with the Improved Dual Neural Network
Introduction
Problem Formulation
The Improved Dual Neural Network
Architecture
Comparison with Other Neural Networks
Stability and Convergence
Numerical Simulations
Concluding Remarks
Evaluating Model on Effectiveness of Network Defense Missile Based on LMBP Neural Network
Introduction
Evaluating Index System of the Operational Effectiveness for the Netting Air-Defense Missile System
Evaluating Model on the Operational Capacity of the Netting Air-Defense Missile System Based on LMBP NN
Neural Net and LMBP Algorithm
Evaluating Model Based on LMBP NN
Analysis of a Real Example
Conclusion
References
A New Neural Network for Solving Nonlinear Programming Problems
Introduction
Problem and the Neural Network Model
Stability Analysis
Numerical Examples
Conclusion
References
The AIC Based on the Neural Network Filter
Introduction
AIC Based on the MLP
Stochastic Gradient BP Algorithm
Computer Simulation
Conclusion
References
Ranked Neuro Fuzzy Inference System (RNFIS) for Information Retrieval
Introduction
Proposed Scheme
Weighted Zone Scoring
Semantic Matching
Fuzzy Linguistic Variables
Fuzzy Inference System
Experimental Results and Evaluation
Document Corpus
FIS Training
Evaluation Parameters
Conclusion
References
The Study on Models Adjustment and Generation Capability of Artificial Neural Network
Introduction
Model's Parameters Adjustment
Model's Architecture Adjustment
Generalization Capabilities
Conclusions
References
Supervised Learning
View Construction for Multi-view Semi-supervised Learning
Introduction
Multi-view Semi-supervised Learning
View Construction
Feature Selection Using GAs
Determining Two Views
Multi-task Learning
Experiments
Single-Task Classifiers
Multi-task Classifiers
Conclusions
References
Fast Learning Fully Complex-Valued Classifiers for Real-Valued Classification Problems
Introduction
Description of the Classifiers
Classification Problem Definition
Fast Learning Complex-Valued Classifiers
Performance Evaluation
Conclusion
References
Urban Stormwater Runoff Prediction Using Recurrent Neural Networks
Introduction
Data and Methods
Study Area and Stormwater Runoff Data
Network Architecture
Network Learning Algorithm
Experimental Results
Error Autocorrelation Function
Input-Error Cross-Correlation Function
Time Series Response
Conclusions
References
Maximal-Margin Approach for Cost-Sensitive Learning Based on Scaled Convex Hull
Introduction
Scaled Convex Hull
SCH for Cost-Sensitive
The MDM Algorithm for SCH Classifier
Experiments
Conclusions
References
Author Index

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