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Abstract
Neural networks are structures consisting of highly interconnected elementary computational units. The network map input patterns into output patterns. These devices are called neural not because they model the nervous systems but because they are inspired by them. Due to their features (adaptive behaviour, learning process, robustness,...) , artificial neural networks have interested the anticipatory systems field of research. In particular, we will examine their interests in the field of time series prediction and system identification.
Text
References
Bibliographical reference
Jean-Philippe Draye, « Artificial neural networks and anticipatory systems », CASYS, 1 | 1998, 179-188.
Electronic reference
Jean-Philippe Draye, « Artificial neural networks and anticipatory systems », CASYS [Online], 1 | 1998, Online since 28 June 2024, connection on 26 December 2024. URL : http://popups.uliege.be/3041-539x/index.php?id=637
Author
Jean-Philippe Draye
Senior Research Assistant of the Belgian National Fund for Scientific Research (F.N.R.S.)
Faculté Polytechnique de Mons, "Parallel Information Processing" Laboratory, Rue de Houdain, 9, 7000 Mons (Belgium)