Artificial Neural Networks - ICANN 2006

Neural Network with Bump Formations.- Error Entropy Minimization for LSTM Training.- Ensemble Learning.- Can AdaBoost.M1 Learn Incrementally? A Comparison to 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 Analysis.- Recurrent Neural Networks Are Universal Approximators.- 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.