{"title":"中子监测仪数据局部间歇测量分析","authors":"A. MacKinnon, Sam Rennie","doi":"10.38072/2748-3150/p16","DOIUrl":null,"url":null,"abstract":"\n Local Intermittency Measure (LIM) is a development of wavelet analysis particularly suited to the diagnosis of isolated, intermittent events in time series. We construct LIM scalograms \n of Neutron Monitor (NM) data for an example each of a large GLE and a Forbush decrease. Both kinds of event show distinctive LIM signatures. In the case of the Forbush decrease the \n method also identifies a second, much smaller event that took place in the same time period. LIM may thus be a useful tool for automated or semi-automated detection of such events in NM data.\n","PeriodicalId":249025,"journal":{"name":"NMDB@Home 2020","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Local intermittency measure analysis of neutron monitor data\",\"authors\":\"A. MacKinnon, Sam Rennie\",\"doi\":\"10.38072/2748-3150/p16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Local Intermittency Measure (LIM) is a development of wavelet analysis particularly suited to the diagnosis of isolated, intermittent events in time series. We construct LIM scalograms \\n of Neutron Monitor (NM) data for an example each of a large GLE and a Forbush decrease. Both kinds of event show distinctive LIM signatures. In the case of the Forbush decrease the \\n method also identifies a second, much smaller event that took place in the same time period. LIM may thus be a useful tool for automated or semi-automated detection of such events in NM data.\\n\",\"PeriodicalId\":249025,\"journal\":{\"name\":\"NMDB@Home 2020\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NMDB@Home 2020\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.38072/2748-3150/p16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NMDB@Home 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38072/2748-3150/p16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Local intermittency measure analysis of neutron monitor data
Local Intermittency Measure (LIM) is a development of wavelet analysis particularly suited to the diagnosis of isolated, intermittent events in time series. We construct LIM scalograms
of Neutron Monitor (NM) data for an example each of a large GLE and a Forbush decrease. Both kinds of event show distinctive LIM signatures. In the case of the Forbush decrease the
method also identifies a second, much smaller event that took place in the same time period. LIM may thus be a useful tool for automated or semi-automated detection of such events in NM data.