{"title":"Testing for presence of kth-rder cyclostationarity","authors":"A. V. Dandawate","doi":"10.1109/HOST.1993.264559","DOIUrl":null,"url":null,"abstract":"The presence of kth-order cyclostationarity is defined in terms of nonvanishing cyclic cumulants and polyspectra. By exploiting the asymptotic normality and consistency of kth-order sample cyclic statistics, asymptotically optimal chi /sup 2/ tests are developed to detect presence of cycles in the kth-order cyclic- cumulants and polyspectra, without assuming any specific distribution on the data. Statistical tests are derived in both time- and frequency-domain and yield consistent estimates of possible cycles present in the kth-order cyclic-statistics. Explicit algorithms for k<or=4 are discussed. Existing approaches are rather empirical and deal only with k<or=2 case. Simulation results are presented to confirm the performance of the given tests.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1993.264559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The presence of kth-order cyclostationarity is defined in terms of nonvanishing cyclic cumulants and polyspectra. By exploiting the asymptotic normality and consistency of kth-order sample cyclic statistics, asymptotically optimal chi /sup 2/ tests are developed to detect presence of cycles in the kth-order cyclic- cumulants and polyspectra, without assuming any specific distribution on the data. Statistical tests are derived in both time- and frequency-domain and yield consistent estimates of possible cycles present in the kth-order cyclic-statistics. Explicit algorithms for k>