{"title":"基于上采样改进的经验模态分解","authors":"Jialing Mo, Weiping Hu, Shasha Le","doi":"10.1109/ICIS.2014.6912171","DOIUrl":null,"url":null,"abstract":"The paper proposes an improved Empirical Mode Decomposition method based on up-sampling, due to the energy leakage in traditional Empirical Mode Decomposition for insufficient sampling rate(digital domain frequency greater than 0.2). The method uses the signal interpolation to improve sampling rate before EMD, and then recovers the original scale by corresponding down-sampling and low pass filtering. The numerical results show that it can partly recover the accurate position of extreme points and effectively reduce the energy leakage. Three typical interpolations are also employed and the result shows that the effect of using cubic spline interpolation with 4 times is the best relatively.","PeriodicalId":237256,"journal":{"name":"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Improving Empirical Mode Decomposition based on up-sampling\",\"authors\":\"Jialing Mo, Weiping Hu, Shasha Le\",\"doi\":\"10.1109/ICIS.2014.6912171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proposes an improved Empirical Mode Decomposition method based on up-sampling, due to the energy leakage in traditional Empirical Mode Decomposition for insufficient sampling rate(digital domain frequency greater than 0.2). The method uses the signal interpolation to improve sampling rate before EMD, and then recovers the original scale by corresponding down-sampling and low pass filtering. The numerical results show that it can partly recover the accurate position of extreme points and effectively reduce the energy leakage. Three typical interpolations are also employed and the result shows that the effect of using cubic spline interpolation with 4 times is the best relatively.\",\"PeriodicalId\":237256,\"journal\":{\"name\":\"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIS.2014.6912171\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIS.2014.6912171","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving Empirical Mode Decomposition based on up-sampling
The paper proposes an improved Empirical Mode Decomposition method based on up-sampling, due to the energy leakage in traditional Empirical Mode Decomposition for insufficient sampling rate(digital domain frequency greater than 0.2). The method uses the signal interpolation to improve sampling rate before EMD, and then recovers the original scale by corresponding down-sampling and low pass filtering. The numerical results show that it can partly recover the accurate position of extreme points and effectively reduce the energy leakage. Three typical interpolations are also employed and the result shows that the effect of using cubic spline interpolation with 4 times is the best relatively.