{"title":"利用经验模态分解的变化来去除信号中的噪声","authors":"M. Kaleem, A. Guergachi, S. Krishnan, A. Çetin","doi":"10.1109/ICNF.2011.5994279","DOIUrl":null,"url":null,"abstract":"This paper will describe the application of τ-based decomposition, which is a variation of the empirical mode decomposition method based on modified peak selection, to de-noising and de-trending of signals. The τ-based decomposition method will be explained, and its application to synthetic and real-world signals in the context of de-noising and de-trending will be described. Comparison between the computational simplicity of the τ-based decomposition method to de-noising and de-trending of signals and approaches based on empirical mode decomposition will be highlighted.","PeriodicalId":137085,"journal":{"name":"2011 21st International Conference on Noise and Fluctuations","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Using a variation of empirical mode decomposition to remove noise from signals\",\"authors\":\"M. Kaleem, A. Guergachi, S. Krishnan, A. Çetin\",\"doi\":\"10.1109/ICNF.2011.5994279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper will describe the application of τ-based decomposition, which is a variation of the empirical mode decomposition method based on modified peak selection, to de-noising and de-trending of signals. The τ-based decomposition method will be explained, and its application to synthetic and real-world signals in the context of de-noising and de-trending will be described. Comparison between the computational simplicity of the τ-based decomposition method to de-noising and de-trending of signals and approaches based on empirical mode decomposition will be highlighted.\",\"PeriodicalId\":137085,\"journal\":{\"name\":\"2011 21st International Conference on Noise and Fluctuations\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 21st International Conference on Noise and Fluctuations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNF.2011.5994279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 21st International Conference on Noise and Fluctuations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNF.2011.5994279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using a variation of empirical mode decomposition to remove noise from signals
This paper will describe the application of τ-based decomposition, which is a variation of the empirical mode decomposition method based on modified peak selection, to de-noising and de-trending of signals. The τ-based decomposition method will be explained, and its application to synthetic and real-world signals in the context of de-noising and de-trending will be described. Comparison between the computational simplicity of the τ-based decomposition method to de-noising and de-trending of signals and approaches based on empirical mode decomposition will be highlighted.
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