Gai Qiang, Ma Xiaojiang, Zhang Haiyong, Zou Yankun
{"title":"一种处理时变信号的新方法","authors":"Gai Qiang, Ma Xiaojiang, Zhang Haiyong, Zou Yankun","doi":"10.1109/ICR.2001.984881","DOIUrl":null,"url":null,"abstract":"The concept of an empirical mode decomposition method with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions (IMF) is introduced. This method is used for time-varying signal analysis and provide a better joint time-frequency resolution than other methods like the STFT, wavelet and the Wigner-Ville distribution. Then we bring forward a new principle of the local wave method and the expression of the intrinsic mode function. We also introduce our new signal decomposition method called local mean mode decomposition (LMMD) which can provide better data mean and results.","PeriodicalId":366998,"journal":{"name":"2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Processing time-varying signals by a new method\",\"authors\":\"Gai Qiang, Ma Xiaojiang, Zhang Haiyong, Zou Yankun\",\"doi\":\"10.1109/ICR.2001.984881\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The concept of an empirical mode decomposition method with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions (IMF) is introduced. This method is used for time-varying signal analysis and provide a better joint time-frequency resolution than other methods like the STFT, wavelet and the Wigner-Ville distribution. Then we bring forward a new principle of the local wave method and the expression of the intrinsic mode function. We also introduce our new signal decomposition method called local mean mode decomposition (LMMD) which can provide better data mean and results.\",\"PeriodicalId\":366998,\"journal\":{\"name\":\"2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICR.2001.984881\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICR.2001.984881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The concept of an empirical mode decomposition method with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions (IMF) is introduced. This method is used for time-varying signal analysis and provide a better joint time-frequency resolution than other methods like the STFT, wavelet and the Wigner-Ville distribution. Then we bring forward a new principle of the local wave method and the expression of the intrinsic mode function. We also introduce our new signal decomposition method called local mean mode decomposition (LMMD) which can provide better data mean and results.