Art neural networks for brain pathology diagnosis

LORCHENKOV, Alexandr

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Facultatea Calculatoare, Informatică şi Microelectronică
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dc.contributor.author	LORCHENKOV, Alexandr
dc.date.accessioned	2019-11-13T11:37:49Z
dc.date.available	2019-11-13T11:37:49Z
dc.date.issued	2005
dc.identifier.citation	LORCHENKOV, Alexandr. Art neural networks for brain pathology diagnosis. In: Microelectronics and Computer Science: proc. of the 4th intern. conf., September 15-17, 2005. Chişinău, 2005, vol. 2, pp. 293-296. ISBN 9975-66-038-X.	en_US
dc.identifier.isbn	9975-66-038-X
dc.identifier.uri	http://repository.utm.md/handle/5014/6762
dc.description.abstract	The present paper is devoted to the questions of the electroencephalograms (EEG) classification. The main objective of the work is ART Neural Network method as applied to the EEG clustering. The first section reviews the problem of epilepsy diagnostics. Then the algorithm based on the ART model is described. Adaptive Resonance Theory ( ART1) Neural Networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic target recognition, medical diagnosis. The paper describes ART1 model for recognition EEG patterns while diagnosing brain diseases.	en_US
dc.language.iso	en	en_US
dc.publisher	Technical University of Moldova	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	neural network models	en_US
dc.subject	cluster algorithm	en_US
dc.subject	algorithms	en_US
dc.subject	electroencephalograms	en_US
dc.subject	epilepsy	en_US
dc.title	Art neural networks for brain pathology diagnosis	en_US
dc.type	Article	en_US