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dc.date2017
dc.date.accessioned2025-08-22T12:19:45Z-
dc.date.available2025-08-22T12:19:45Z-
dc.date.issued2017
dc.identifier.identifierDspace\SGAU\20170523\64148
dc.identifier.citationMandrikova O. Method of ionospheric data analysis based on a combination of wavelet transform and neural networks / O. Mandrikova, Yu. Polozov, V. Geppener // Сборник трудов III международной конференции и молодежной школы «Информационные технологии и нанотехнологии» (ИТНТ-2017) - Самара: Новая техника, 2017. - С. 1767-1773.
dc.identifier.urihttp://repo.ssau.ru/jspui/handle/123456789/13556-
dc.description.abstractThe paper presents a hybrid system based on a combination of wavelet filtering operations and regression neural networks. The system is adapted to analyze the ionosphere data obtained at "Paratunka" station (Kamchatka). Testing of the system has shown its efficiency in the tasks of analysis of characteristic properties of ionospheric data and detection of anomalies occurring during disturbed periods. For a detailed analysis of anomalies, computing solutions based on the application of continuous wavelet transform and threshold functions were suggested. The developed computational tools were implemented in software environment.
dc.description.sponsorshipThe research was supported by RSF Grant №14-11-00194.
dc.languageen
dc.publisherНовая техника
dc.titleMethod of ionospheric data analysis based on a combination of wavelet transform and neural networks
dc.typeArticle
local.identifier.oldurihttp://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148
local.identifier.oldurihttp://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148
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