Method of ionospheric data analysis based on a combination of wavelet transform and neural networks
The 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 analysi...
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Новая техника
2017
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Online Access: | http://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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ftsamarauniv:oai:repo.ssau.ru:Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148 |
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ftsamarauniv:oai:repo.ssau.ru:Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148 2023-10-29T02:37:34+01:00 Method of ionospheric data analysis based on a combination of wavelet transform and neural networks Mandrikova, O. Polozov, Yu. Geppener, V. 2017 http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148 en eng Новая техника Dspace\SGAU\20170523\64148 Mandrikova 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. http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148 wavelet-transform neural networks critical frequency of the ionosphere ionospheric storms anomalies magnetic storms Article 2017 ftsamarauniv 2023-10-03T08:15:13Z The 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. The research was supported by RSF Grant №14-11-00194. Article in Journal/Newspaper Kamchatka Samara University: Repository |
institution |
Open Polar |
collection |
Samara University: Repository |
op_collection_id |
ftsamarauniv |
language |
English |
topic |
wavelet-transform neural networks critical frequency of the ionosphere ionospheric storms anomalies magnetic storms |
spellingShingle |
wavelet-transform neural networks critical frequency of the ionosphere ionospheric storms anomalies magnetic storms Mandrikova, O. Polozov, Yu. Geppener, V. Method of ionospheric data analysis based on a combination of wavelet transform and neural networks |
topic_facet |
wavelet-transform neural networks critical frequency of the ionosphere ionospheric storms anomalies magnetic storms |
description |
The 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. The research was supported by RSF Grant №14-11-00194. |
format |
Article in Journal/Newspaper |
author |
Mandrikova, O. Polozov, Yu. Geppener, V. |
author_facet |
Mandrikova, O. Polozov, Yu. Geppener, V. |
author_sort |
Mandrikova, O. |
title |
Method of ionospheric data analysis based on a combination of wavelet transform and neural networks |
title_short |
Method of ionospheric data analysis based on a combination of wavelet transform and neural networks |
title_full |
Method of ionospheric data analysis based on a combination of wavelet transform and neural networks |
title_fullStr |
Method of ionospheric data analysis based on a combination of wavelet transform and neural networks |
title_full_unstemmed |
Method of ionospheric data analysis based on a combination of wavelet transform and neural networks |
title_sort |
method of ionospheric data analysis based on a combination of wavelet transform and neural networks |
publisher |
Новая техника |
publishDate |
2017 |
url |
http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148 |
genre |
Kamchatka |
genre_facet |
Kamchatka |
op_relation |
Dspace\SGAU\20170523\64148 Mandrikova 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. http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Method-of-ionospheric-data-analysis-based-on-a-combination-of-wavelet-transform-and-neural-networks-64148 |
_version_ |
1781062473942564864 |