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Art neural networks for brain pathology diagnosis

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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


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