{"title":"用典型相关分析检测非平稳过程的多锥度检验","authors":"F. A. Marshall, G. Takahara, D. Thomson","doi":"10.1109/SSP.2018.8450806","DOIUrl":null,"url":null,"abstract":"A new test has been designed for detecting the presence of non-stationary component processes in a time series. The test statistic is derived from the canonical correlations between two sets of eigencoefficients which are offset in frequency. The correlation coefficient which defines the test statistic has lower estimation variance than the multitaper, linear spectral-correlation coefficient, and it reveals important evidence of non-stationarity which is missed in the detector of the latter correlation coefficient.","PeriodicalId":330528,"journal":{"name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Multitaper Test For The Detection of Non-Stationary Processes Using Canonical Correlation Analysis\",\"authors\":\"F. A. Marshall, G. Takahara, D. Thomson\",\"doi\":\"10.1109/SSP.2018.8450806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new test has been designed for detecting the presence of non-stationary component processes in a time series. The test statistic is derived from the canonical correlations between two sets of eigencoefficients which are offset in frequency. The correlation coefficient which defines the test statistic has lower estimation variance than the multitaper, linear spectral-correlation coefficient, and it reveals important evidence of non-stationarity which is missed in the detector of the latter correlation coefficient.\",\"PeriodicalId\":330528,\"journal\":{\"name\":\"2018 IEEE Statistical Signal Processing Workshop (SSP)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Statistical Signal Processing Workshop (SSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSP.2018.8450806\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Statistical Signal Processing Workshop (SSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSP.2018.8450806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multitaper Test For The Detection of Non-Stationary Processes Using Canonical Correlation Analysis
A new test has been designed for detecting the presence of non-stationary component processes in a time series. The test statistic is derived from the canonical correlations between two sets of eigencoefficients which are offset in frequency. The correlation coefficient which defines the test statistic has lower estimation variance than the multitaper, linear spectral-correlation coefficient, and it reveals important evidence of non-stationarity which is missed in the detector of the latter correlation coefficient.
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