§16§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. In 2006 the ICANN Conference was organized by the Intelligent Systems Laboratory and the Image, Video and Multimedia Systems Laboratory of the National Technical University of §16§Athens in Athens, Greece. From 475 papers submitted to the conference, the International Program Committee selected, following a thorough peer-review process, 208 papers for publication and presentation to 21 regular and 10 special sessions. The quality of the papers received was in general very high; as a consequence, it was not possible to accept and include in the conference program many papers of good quality. §04§Feature Selection and Dimension Reduction for Regression (Special Session).- Learning Algorithms (I).- Learning Algorithms (II).- Advances in Neural Network Learning Methods (Special Session).- Ensemble Learning.- Learning Random Neural Networks and Stochastic Agents (Special Session).- Hybrid Architectures.- Self Organization.- Connectionist Cognitive Science.- Cognitive Machines (Special Session).- Neural Dynamics and Complex Systems.- Computational Neuroscience.- Neural Control, Reinforcement Learning and Robotics Applications.- Robotics, Control, Planning.- Bio-inspired Neural Network On-Chip Implementation and Applications (Special session). §02§ERKKI OJA is professor at the Neural Networks Research Center of Helsinki University of Technology in Finland.§ §04§ 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 Acti
