Kollias S., Stafylopatis A., Duch W., Oja E. (eds.) Artificial Neural Networks, ICANN 2006, Part I

Springer, 2006. — 1041 p.16th International Conference. Athens, Greece, September 10-14, 2006 Proceedings, Part I.
This book includes the proceedings of the International Conference on Artificial Neural Networks (ICANN 2006) held on September 10-14, 2006 in Athens, Greece, with tutorials being presented on September 10, the main conference taking place during September 11-13 and accompanying workshops on perception, cognition and interaction held on September 14, 2006.
The ICANN conference is organized annually by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas. The ICANN series of conferences was initiated in 1991 and soon became the major European gathering for experts in these fields.Feature Selection and Dimension Reduction for Regression (Special Session)
Dimensionality Reduction Based on ICA for Regression Problems
A Functional Approach to Variable Selection in Spectrometric Problems
The Bayes-Optimal Feature Extraction Procedure for Pattern Recognition Using Genetic Algorithm
Speeding Up the Wrapper Feature Subset Selection in Regression by Mutual Information Relevance and Redundancy Analysis
Effective Input Variable Selection for Function Approximation
Comparative Investigation on Dimension Reduction and Regression in Three Layer Feed-Forward Neural Network
Learning Algorithms (I)
On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition
Learning Long Term Dependencies with Recurrent Neural Networks
Adaptive On-Line Neural Network Retraining for Real Life Multimodal Emotion Recognition
Time Window Width Influence on Dynamic BPTT(h) Learning Algorithm Performances: Experimental Study
Framework for the Interactive Learning of Artificial Neural Networks
Analytic Equivalence of Bayes a Posteriori Distributions
Learning Algorithms (II)
Neural Network Architecture Selection: Size Depends on Function Complexity
Competitive Repetition-suppression (CoRe) Learning
Real-Time Construction of Neural Networks
MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation
A Variational Formulation for the Multilayer Perceptron
Advances in Neural Network Learning Methods (Special Session)
Natural Conjugate Gradient Training of Multilayer Perceptrons
Building Ensembles of Neural Networks with Class-Switching
K-Separability
Lazy Training of Radial Basis Neural Networks
Investigation of Topographical Stability of the Concave and Convex Self-Organizing Map Variant
Alternatives to Parameter Selection for Kernel Methods
Faster Learning with Overlapping Neural Assemblies
Improved Storage Capacity of Hebbian Learning Attractor Neural Network with Bump Formations
Error Entropy Minimization for LSTM Training
Ensemble Learning
Can AdaBoost.M1 Learn Incrementally? A Comparison Learn++ Under Different Combination Rules
Ensemble Learning with Local Diversity
A Machine Learning Approach to Define Weights for Linear Combination of Forecasts
A Game-Theoretic Approach to Weighted Majority Voting for Combining SVM Classifiers
Improving the Expert Networks of a Modular Multi-Net System for Pattern Recognition
Learning Random Neural Networks and Stochastic Agents (Special Session)
Evaluating Users’ Satisfaction in Packet Networks Using Random Neural Networks
Random Neural Networks for the Adaptive Control of Packet Networks
Hardware Implementation of Random Neural Networks with Reinforcement Learning
G-Networks and the Modeling of Adversarial Agents
Hybrid Architectures
Development of a Neural Net-Based, Personalized Secure Communication Link
Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees
Active Learning with the Probabilistic RBF Classifier
Merging Echo State and Feedforward Neural Networks for Time Series Forecasting
Language and Cognition Integration Through Modeling Field Theory: Category Formation for Symbol Grounding
A Methodology for Estimating the Product Life Cycle Cost Using a Hybrid GA and ANN Model
Self Organization
Using Self-Organizing Maps to Support Video Navigation
Self-Organizing Neural Networks for Signal Recognition
An Unsupervised Learning Rule for Class Discrimination in a Recurrent Neural Network
On the Variants of the Self-Organizing Map That Are Based on Order Statistics
On the Basis Updating Rule of Adaptive-Subspace Self-Organizing Map (ASSOM)
Composite Algorithm for Adaptive Mesh Construction Based on Self-Organizing Maps
A Parameter in the Learning Rule of SOM That Incorporates Activation Frequency
Nonlinear Projection Using Geodesic Distances and the Neural Gas Network
Connectionist Cognitive Science
Contextual Learning in the Neurosolver
A Computational Model for the Effect of Dopamine on Action Selection During Stroop Test
A Neural Network Model of Metaphor Understanding with Dynamic Interaction Based on a Statistical Language Analysis
Strong Systematicity in Sentence Processing by an Echo State Network
Modeling Working Memory and Decision Making Using Generic Neural Microcircuits
A Virtual Machine for Neural Computers
Cognitive Machines (Special Session)
Machine Cognition and the EC Cognitive Systems Projects: Now and in the Future
A Complex Neural Network Model for Memory Functioning in Psychopathology
Modelling Working Memory Through Attentional Mechanisms
A Cognitive Model of Multi-objective Multi-concept Formation
A Basis for Cognitive Machines
Neural Model of Dopaminergic Control of Arm Movements in Parkinson’s Disease Bradykinesia
Occlusion, Attention and Object Representations
A Forward / Inverse Motor Controller for Cognitive Robotics
A Computational Model for Multiple Goals
Neural Dynamics and Complex Systems
Detection of a Dynamical System Attractor from Spike Train
Recurrent Neural Networks Are Universal
A Discrete Adaptive Stochastic Neural Model for Constrained Optimization
Quantum Perceptron Network
Critical Echo State Networks
Rapid Correspondence Finding in Networks of Cortical Columns
Adaptive Thresholds for Layered Neural Networks with Synaptic Noise
Backbone Structure of Hairy Memory
Dynamics of Citation Networks
Computational Neuroscience
Processing of Information in Synchroneously Firing Chains in Networks of Neurons
Phase Precession and Recession with STDP and Anti-STDP
Visual Pathways for Detection of Landmark Points
A Model of Grid Cells Based on a Path Integration Mechanism
Temporal Processing in a Spiking Model of the Visual System
Accelerating Event Based Simulation for Multi-synapse Spiking Neural Networks
A Neurocomputational Model of an Imitation Deficit Following Brain Lesion
Temporal Data Encoding and SequenceLearning with Spiking Neural Networks
Neural Control, Reinforcement Learning and Robotics Applications
Optimal Tuning of Continual Online Exploration in Reinforcement Learning
Vague Neural Network Controller and Its Applications
Parallel Distributed Profit Sharing for PC Cluster
Feature Extraction for Decision-Theoretic Planning in Partially Observable Environments
Reinforcement Learning with Echo State Networks
Reward Function and Initial Values: Better Choices for Accelerated Goal-Directed Reinforcement Learning
Nearly Optimal Exploration-Exploitation Decision Thresholds
Dual Adaptive ANN Controllers Based on Wiener Models for Controlling Stable Nonlinear Systems
Online Stabilization of Chaotic Maps Via Support Vector Machines Based Generalized Predictive Control
Robotics, Control, Planning
Morphological Neural Networks and Vision Based Mobile Robot Navigation
Position Control Based on Static Neural Networks of Anthropomorphic Robotic Fingers
Learning Multiple Models of Non-linear Dynamics for Control Under Varying Contexts
A Study on Optimal Configuration for the Mobile Manipulator: Using Weight Value and Mobility
VSC Perspective for Neurocontroller Tuning
A Neural Network Module with Pretuning for Search and Reproduction of Input-Output Mapping
Bio-inspired Neural Network On-Chip Implementation and Applications (Special session)
Physical Mapping of Spiking Neural Networks Models on a Bio-inspired Scalable Architecture
A Time Multiplexing Architecture for Inter-neuron Communications
Neuronal Cell Death and Synaptic Pruning Driven by Spike-Timing Dependent Plasticity
Effects of Analog-VLSI Hardware on the Performance of the LMS Algorithm
A Portable Electronic Nose (E-Nose) System Based on PDA
Optimal Synthesis of Boolean Functions by Threshold Functions
Pareto-optimal Noise and Approximation Properties of RBF Networks