{"title":"噪声中周期信号的检测:一个迭代过程","authors":"H.J Heinze, H Künkel, W Massing","doi":"10.1016/0010-468X(84)90038-2","DOIUrl":null,"url":null,"abstract":"<div><p>A method for detection and estimation of periodic signals in the presence of noise is described. The algorithm is an iterative improvement of the autoregressive-moving average estimation of a stochastic process and gives an exact frequency resolution of sinusoidal signals additively mixed with noise in a low signal-to-noise ratio only from a small number of measurements. The iterative improvement of the spectral estimation compared with other methods is demonstrated by examples.</p></div>","PeriodicalId":75731,"journal":{"name":"Computer programs in biomedicine","volume":"19 1","pages":"Pages 55-59"},"PeriodicalIF":0.0000,"publicationDate":"1984-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0010-468X(84)90038-2","citationCount":"3","resultStr":"{\"title\":\"Detection of periodic signals in noise: an iterative procedure\",\"authors\":\"H.J Heinze, H Künkel, W Massing\",\"doi\":\"10.1016/0010-468X(84)90038-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A method for detection and estimation of periodic signals in the presence of noise is described. The algorithm is an iterative improvement of the autoregressive-moving average estimation of a stochastic process and gives an exact frequency resolution of sinusoidal signals additively mixed with noise in a low signal-to-noise ratio only from a small number of measurements. The iterative improvement of the spectral estimation compared with other methods is demonstrated by examples.</p></div>\",\"PeriodicalId\":75731,\"journal\":{\"name\":\"Computer programs in biomedicine\",\"volume\":\"19 1\",\"pages\":\"Pages 55-59\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1984-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0010-468X(84)90038-2\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer programs in biomedicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0010468X84900382\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer programs in biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0010468X84900382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of periodic signals in noise: an iterative procedure
A method for detection and estimation of periodic signals in the presence of noise is described. The algorithm is an iterative improvement of the autoregressive-moving average estimation of a stochastic process and gives an exact frequency resolution of sinusoidal signals additively mixed with noise in a low signal-to-noise ratio only from a small number of measurements. The iterative improvement of the spectral estimation compared with other methods is demonstrated by examples.
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