{"title":"基于emd的信号频域分辨率研究","authors":"Meng Hou, Zeng-li Liu, Haiyan Quan, Yong-de Zhang","doi":"10.1109/CIS.2010.151","DOIUrl":null,"url":null,"abstract":"Empirical Mode Decomposition (EMD) is an effective, non-linear and non-stationary data analysis method, which can decompose the original signal into several intrinsic mode functions(IMFs). However the frequency resolution of EMD has not been thoroughly investigated so far. In this paper a signal which contains two different frequency components was do composed with EMD, and subsequently the obtained IMFs was compared to evaluate the frequency resolution of EMD.","PeriodicalId":420515,"journal":{"name":"2010 International Conference on Computational Intelligence and Security","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Research of Signal Frequency Domain Resolution Based-EMD\",\"authors\":\"Meng Hou, Zeng-li Liu, Haiyan Quan, Yong-de Zhang\",\"doi\":\"10.1109/CIS.2010.151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Empirical Mode Decomposition (EMD) is an effective, non-linear and non-stationary data analysis method, which can decompose the original signal into several intrinsic mode functions(IMFs). However the frequency resolution of EMD has not been thoroughly investigated so far. In this paper a signal which contains two different frequency components was do composed with EMD, and subsequently the obtained IMFs was compared to evaluate the frequency resolution of EMD.\",\"PeriodicalId\":420515,\"journal\":{\"name\":\"2010 International Conference on Computational Intelligence and Security\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Computational Intelligence and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2010.151\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Computational Intelligence and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2010.151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research of Signal Frequency Domain Resolution Based-EMD
Empirical Mode Decomposition (EMD) is an effective, non-linear and non-stationary data analysis method, which can decompose the original signal into several intrinsic mode functions(IMFs). However the frequency resolution of EMD has not been thoroughly investigated so far. In this paper a signal which contains two different frequency components was do composed with EMD, and subsequently the obtained IMFs was compared to evaluate the frequency resolution of EMD.
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