This volume is part of the two-volume proceedings of the 19th International Conf- ence on
Artificial Neural Networks (ICANN 2009) which was held in Cyprus during September 14¿17 2009.
The ICANN conference is an annual meeting sp- sored by the European Neural Network Society
(ENNS) in cooperation with the - ternational Neural Network Society (INNS) and the Japanese
Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational
Intel- gence 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.
Artificial neural networks provide an information-processing structure inspired by biological
nervous systems. They consist of a large number of highly interconnected processing elements
with the capability of learning by example. The field of artificial neural networks has evolved
significantly in the last two decades with active partici- tion from diverse fields such as
engineering computer science mathematics artificial intelligence system theory biology
operations research and neuroscience. Artificial neural networks have been widely applied for
pattern recognition control optimization image processing classification signal processing
etc.
