{"title":"惠特尔定理在环平稳信号中的推广","authors":"S. V. Schell","doi":"10.1109/SSAP.1992.246860","DOIUrl":null,"url":null,"abstract":"Whittle's theorem greatly facilitates the computation of the Cramer-Rao bound (CRB) for stationary signals by establishing that the Fisher information matrix can be asymptotically re-expressed in terms of the spectral density matrix, which for stationary signals is diagonal and thus is easily invertible. A generalization that accommodates cyclostationary signals is proposed, and examples of its application to computing the CRB for parameters of cyclostationary signals are given.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Generalization of Whittle's theorem to cyclostationary signals\",\"authors\":\"S. V. Schell\",\"doi\":\"10.1109/SSAP.1992.246860\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Whittle's theorem greatly facilitates the computation of the Cramer-Rao bound (CRB) for stationary signals by establishing that the Fisher information matrix can be asymptotically re-expressed in terms of the spectral density matrix, which for stationary signals is diagonal and thus is easily invertible. A generalization that accommodates cyclostationary signals is proposed, and examples of its application to computing the CRB for parameters of cyclostationary signals are given.<<ETX>>\",\"PeriodicalId\":309407,\"journal\":{\"name\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSAP.1992.246860\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSAP.1992.246860","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generalization of Whittle's theorem to cyclostationary signals
Whittle's theorem greatly facilitates the computation of the Cramer-Rao bound (CRB) for stationary signals by establishing that the Fisher information matrix can be asymptotically re-expressed in terms of the spectral density matrix, which for stationary signals is diagonal and thus is easily invertible. A generalization that accommodates cyclostationary signals is proposed, and examples of its application to computing the CRB for parameters of cyclostationary signals are given.<>