Guest Editors' Introduction
On the Stability of Source Separation Algorithms
Blind Source Separation for Non-Stationary Mixing
Flexible Independent Component Analysis
On-line Convolutive Blind Source Separation of Non-Stationary Signals
Gradient Adaptive Algorithms for Contrast-Based Blind Deconvolution*
Learning from Examples with Information Theoretic Criteria
Hill-Climbing, Density-Based Clustering and Equiprobabilistic Topographic Maps
Assessing the Number of Components in Finite Gaussian Mixtures by Generalised Fisher Ratio, Normalised Entropy Criterion and Functional Merging*
Advanced RNN Based NARMA Predictors
Dynamic Learning with the EM Algorithm for Neural Networks
Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates
A General Probabilistic Formulation for Supervised Neural Classifiers
Adaptive Metric Kernel Regression
Neural Network Modelling with Input Uncertainty