| 5 | -- | 6 | Tülay Adali, Marc M. Van Hulle, Mahasan Niranjan. Guest Editors Introduction |
| 7 | -- | 14 | Jean-François Cardoso. On the Stability of Source Separation Algorithms |
| 15 | -- | 23 | Richard Everson, Stephen Roberts. Blind Source Separation for Non-Stationary Mixing |
| 25 | -- | 38 | Seungjin Choi, Andrzej Cichocki, Shun-ichi Amari. Flexible Independent Component Analysis |
| 39 | -- | 46 | Lucas C. Parra, Clay Spence. On-line Convolutive Blind Source Separation of Non-Stationary Signals |
| 47 | -- | 60 | Scott C. Douglas, S. Y. Kung. Gradient Adaptive Algorithms for Contrast-Based Blind Deconvolution |
| 61 | -- | 77 | Jose C. Principe, Dongxin Xu, Qun Zhao, John W. Fisher. Learning from Examples with Information Theoretic Criteria |
| 79 | -- | 94 | Marc M. Van Hulle. Hill-Climbing, Density-Based Clustering and Equiprobabilistic Topographic Maps |
| 95 | -- | 103 | Christophe G. Molina. Assessing the Number of Components in Finite Gaussian Mixtures by Generalised Fisher Ratio, Normalised Entropy Criterion and Functional Merging |
| 105 | -- | 117 | Danilo P. Mandic, Jonathon A. Chambers. Advanced RNN Based NARMA Predictors |
| 119 | -- | 131 | João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee. Dynamic Learning with the EM Algorithm for Neural Networks |
| 133 | -- | 140 | Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton. Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates |
| 141 | -- | 153 | Hongmei Ni, Tülay Adali, Bo Wang, Xiao Liu. A General Probabilistic Formulation for Supervised Neural Classifiers |
| 155 | -- | 167 | Cyril Goutte, Jan Larsen. Adaptive Metric Kernel Regression |
| 169 | -- | 188 | W. A. Wright, Guillaume Ramage, Dan Cornford, Ian T. Nabney. Neural Network Modelling with Input Uncertainty: Theory and Application |