Alippi C., Polycarpou M., Panayiotou C., Ellinas G. (eds.) Artificial Neural Networks, ICANN 2009, Part I

Springer, 2009. — 1062 p.19th International Conference. Limassol, Cyprus, September 14-17, 2009 Proceedings, Part I.
This volume is part of the two-volume proceedings of the 19th International Conference on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14–17, 2009. The ICANN conference is an annual meeting sponsored by the European Neural Network Society (ENNS), in cooperation with the International Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intelligence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas.Learning Algorithms
Mutual Information Based Initialization of Forward-Backward Search for Feature Selection in Regression Problems
Kernel Learning for Local Learning Based Clustering
Projective Nonnegative Matrix Factorization with α-Divergence
Active Generation of Training Examples in Meta-Regression
A Maximum-Likelihood Connectionist Model for Unsupervised Learning over Graphical Domains
Local Feature Selection for the Relevance Vector Machine Using Adaptive Kernel Learning
MINLIP: Efficient Learning of Transformation Models
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
Optimal Training Sequences for Locally Recurrent Neural Networks
Statistical Instance-Based Ensemble Pruning for Multi-class Problems
Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes
Mixing Different Search Biases in Evolutionary Learning Algorithms
Semi-supervised Learning for Regression with Co-training by Committee
An Analysis of Meta-learning Techniques for Ranking Clustering Algorithms Applied to Artificial Data
Probability-Based Distance Function for Distance-Based Classifiers
Constrained Learning Vector Quantization or Relaxed k-Separability
Minimization of Quadratic Binary Functional with Additive Connection Matrix
Mutual Learning with Many Linear Perceptrons: On-Line Learning Theory
Computational Neuroscience
Synchrony State Generation in Artificial Neural Networks with Stochastic Synapses
Coexistence of Cell Assemblies and STDP
Controlled and Automatic Processing in Animals and Machines with Application to Autonomous Vehicle Control
Multiple Sound Source Localisation in Reverberant Environments Inspired by the Auditory Midbrain
A Model of Neuronal Specialization Using Hebbian Policy-Gradient with “Slow” Noise
How Bursts Shape the STDP Curve in the Presence/Absence of GABAergic Inhibition
Optimizing Generic Neural Microcircuits through Reward Modulated STDP
Calcium Responses Model in Striatum Dependent on Timed Input Sources
Independent Component Analysis Aided Diagnosis of Cuban Spino Cerebellar Ataxia 2
Hippocampus, Amygdala and Basal Ganglia Based Navigation Control
A Framework for Simulation and Analysis of Dynamically Organized Distributed Neural Networks
Continuous Attractors of Lotka-Volterra Recurrent Neural Networks
Structural Analysis on STDP Neural Networks Using Complex Network Theory
Time Coding of Input Strength Is Intrinsic to Synapses with Short Term Plasticity
Information Processing and Timing Mechanisms in Vision
Review of Neuron Types in the Retina: Information Models for Neuroengineering
Brain Electric Microstate and Perception of Simultaneously Audiovisual Presentation
A Model for Neuronal Signal Representation by Stimulus-Dependent Receptive Fields
Hardware Implementations and Embedded Systems
Area Chip Consumption by a Novel Digital CNN Architecture for Pattern Recognition
Multifold Acceleration of Neural Network Computations Using GPU
Training Recurrent Neural Network Using Multistream Extended Kalman Filter on Multicore Processor and Cuda Enabled Graphic Processor Unit
A Non-subtraction Configuration of Self-similitude Architecture for Multiple-Resolution Edge-Filtering CMOS Image Sensor
Current-Mode Computation with Noise in a Scalable and Programmable Probabilistic Neural VLSI System
Minimising Contrastive Divergence with Dynamic Current Mirrors
Spiking Neural Network Self-configuration for Temporal Pattern Recognition Analysis
Image Recognition in Analog VLSI with On-Chip Learning
Behavior Modeling by Neural Networks
Statistical Parameter Identification of Analog Integrated Circuit Reverse Models
A New FGMOST Euclidean Distance Computational Circuit Based on Algebraic Mean of the Input Potentials
FPGA Implementation of Support Vector Machines for 3D Object Identification
Reconfigurable MAC-Based Architecture for Parallel Hardware Implementation on FPGAs of Artificial Neural Networks Using Fractional Fixed Point Representation
Self Organization
A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means
Image Theft Detection with Self-Organising Maps
Improved Kohonen Feature Map Associative Memory with Area Representation for Sequential Analog Patterns
Surface Reconstruction Method Based on a Growing Self-Organizing Map
Micro-SOM: A Linear-Time Multivariate Microaggregation Algorithm Based on Self-Organizing Maps
Identifying Clusters Using Growing Neural Gas: First Results
Hierarchical Architecture with Modular Network SOM and Modular Reinforcement Learning
Hybrid Systems for River Flood Forecasting Using MLP, SOM and Fuzzy Systems
Topographic Mapping of Astronomical Light Curves via a Physically Inspired Probabilistic Model
Generalized Self-Organizing Mixture Autoregressive Model for Modeling Financial Time Series
Self-Organizing Map Simulations Confirm Similarity of Spatial Correlation Structure in Natural Images and Cortical Representations
Intelligent Control and Adaptive Systems
Height Defuzzification Method on L^∞ Space
An Additive Reinforcement Learning
Neural Spike Suppression by Adaptive Control of an Unknown Steady State
Combined Mechanisms of Internal Model Control and Impedance Control under Force Fields
Neural Network Control of Unknown Nonlinear Systems with Efficient Transient Performance
High-Order Fuzzy Switching Neural Networks: Application to the Tracking Control of a Class of Uncertain SISO Nonlinear Systems
Neural and Hybrid Architectures
A Guide for the Upper Bound on the Number of Continuous-Valued Hidden Nodes of a Feed-Forward Network
Comparative Study of the CG and HBF ODEs Used in the Global Minimization of Nonconvex Functions
On the Knowledge Organization in Concept Formation: An Exploratory Cognitive Modeling Study
Dynamics of Incremental Learning by VSF-Network
Kernel CMAC with Reduced Memory Complexity
Model Complexity of Neural Networks and Integral Transforms
Function Decomposition Network
Improved Storage Capacity in Correlation Matrix Memories Storing Fixed Weight Codes
Multiagent Reinforcement Learning with Spiking and Non-Spiking Agents in the Iterated Prisoner’s Dilemma
Unsupervised Learning in Reservoir Computing: Modeling Hippocampal Place Cells for Small Mobile Robots
Switching Hidden Markov Models for Learning of Motion Patterns in Videos
Multimodal Belief Integration by HMM/SVM-Embedded Bayesian Network: Applications to Ambulating PC Operation by Body Motions and Brain Signals
A Neural Network Model of Metaphor Generation with Dynamic Interaction
Almost Random Projection Machine
Optimized Learning Vector Quantization Classifier with an Adaptive Euclidean Distance
Efficient Parametric Adjustment of Fuzzy Inference System Using Error Backpropagation Method
Neuro-fuzzy Rough Classifier Ensemble
Combining Feature Selection and Local Modelling in the KDD Cup 99 Dataset
An Automatic Parameter Adjustment Method of Pulse Coupled Neural Network for Image Segmentation
Pattern Identification by Committee of Potts Perceptrons
Support Vector Machine
Is Primal Better Than Dual
A Fast BMU Search for Support Vector Machine
European Option Pricing by Using the Support Vector Regression Approach
Learning SVMs from Sloppily Labeled Data
The GMM-SVM Supervector Approach for the Recognition of the Emotional Status from Speech
A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems
Spanning SVM Tree for Personalized Transductive Learning
Improving Text Classification Performance with Incremental Background Knowledge
Empirical Study of the Universum SVM Learning for High-Dimensional Data
Relevance Feedback for Content-Based Image Retrieval Using Support Vector Machines and Feature Selection
Recurrent Neural Network
Understanding the Principles of Recursive Neural Networks: A Generative Approach to Tackle Model Complexity
An EM Based Training Algorithm for Recurrent Neural Networks
Modeling Dst with Recurrent EM Neural Networks
On the Quantification of Dynamics in Reservoir Computing
Solving the CLM Problem by Discrete-Time Linear Threshold Recurrent Neural Networks
Scalable Neural Networks for Board Games
Reservoir Size, Spectral Radius and Connectivity in Static Classification Problems