Geometrical Invariants Approach to Recognition the Structures in Time Series and Abstract Maps
p. 72-80
Résumé
The problem of recognition of geometrical objects in different types of data and signals is considered. The main tool in the proposed methodology is a new definition of a cluster based on the invariants of some transformations of space. The invariant properties are closely connected to the symmetry groups of objects. As an illustration, the classical symmetries of space such as continuous groups (Lie transformations) are considered. The particular case of spike recognition in neurophysiology is described in details. Preliminary investigations show the high potential power of method. The further prospects of the proposed method are discussed including the problem of perception and models of mentality.
Index
Texte
Citer cet article
Référence papier
Anatoliy I. Polyarush, Igor V. Tetko et Alexander S. Makarenko, « Geometrical Invariants Approach to Recognition the Structures in Time Series and Abstract Maps », CASYS, 15 | 2004, 72-80.
Référence électronique
Anatoliy I. Polyarush, Igor V. Tetko et Alexander S. Makarenko, « Geometrical Invariants Approach to Recognition the Structures in Time Series and Abstract Maps », CASYS [En ligne], 15 | 2004, mis en ligne le 17 July 2024, consulté le 20 September 2024. URL : http://popups.lib.uliege.be/1373-5411/index.php?id=1934
Auteurs
Anatoliy I. Polyarush
Bogomolets Institute of Physiology, Bogomolets str.,4, Kyiv, 01024, Ukraine
Igor V. Tetko
Biomedical Department, IBPC, Ukrainian Academy of Sciences, Murmanskaya, 1, Kyiv, 02094, Ukraine and Institute for Bioinformatics, GSF, Ingolstädter Landstraße 1, D-85764, Neuherberg, Germany
Alexander S. Makarenko
Institute for Applied System Analysis, National Technical University of Ukraine (KPI), Pobedy Awenue, 37, 03056, Kyiv-56, Ukraine