{"title":"使用高阶统计量的采样抖动检测","authors":"J. Tourneret, A. Ferrari, B. Lacaze","doi":"10.1109/HOST.1997.613565","DOIUrl":null,"url":null,"abstract":"The spectrum of a signal subjected, to sampling jitter can be significantly different from the spectrum of the same signal sampled without jitter. The first part of the paper shows that the spectrum of a continuous Gaussian signal can be reconstructed from a combined use of the sampled (with jitter) signal second and fourth-order statistics. This spectral reconstruction is then used to detect the presence or absence of jitter in a sampled signal. A likelihood ratio detector based on the spectral corrective term is studied. It gives a reference to which suboptimal detectors can be compared.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sampling jitter detection using higher-order statistics\",\"authors\":\"J. Tourneret, A. Ferrari, B. Lacaze\",\"doi\":\"10.1109/HOST.1997.613565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The spectrum of a signal subjected, to sampling jitter can be significantly different from the spectrum of the same signal sampled without jitter. The first part of the paper shows that the spectrum of a continuous Gaussian signal can be reconstructed from a combined use of the sampled (with jitter) signal second and fourth-order statistics. This spectral reconstruction is then used to detect the presence or absence of jitter in a sampled signal. A likelihood ratio detector based on the spectral corrective term is studied. It gives a reference to which suboptimal detectors can be compared.\",\"PeriodicalId\":305928,\"journal\":{\"name\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1997.613565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sampling jitter detection using higher-order statistics
The spectrum of a signal subjected, to sampling jitter can be significantly different from the spectrum of the same signal sampled without jitter. The first part of the paper shows that the spectrum of a continuous Gaussian signal can be reconstructed from a combined use of the sampled (with jitter) signal second and fourth-order statistics. This spectral reconstruction is then used to detect the presence or absence of jitter in a sampled signal. A likelihood ratio detector based on the spectral corrective term is studied. It gives a reference to which suboptimal detectors can be compared.