{"title":"Labview环境下改进proony方法的平滑滤波器","authors":"Lina El Alaoui El Abidi, M. Hanine, B. Aksasse","doi":"10.1109/ISCV49265.2020.9204174","DOIUrl":null,"url":null,"abstract":"Exponentially decaying signals occur in various parts of nature and affect the performance and flexibility of signals. In fact, that drives scientists to invest in a perpetual search for new solutions. To meet this challenge few methods are proposed. In this study, we focused on the use of the Prony Method and Bessel and Butterworth smoothing methods in the LabVIEW environment for estimating the parameters of a sum of real exponential signals in the presence of noise. The performances of the proposed method are illustrated using simulated data, clearly showing the improved performance of the Prony Method and especially with Butterworth filter.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Smooth Filters for Improving Prony’s Method in Labview Environment\",\"authors\":\"Lina El Alaoui El Abidi, M. Hanine, B. Aksasse\",\"doi\":\"10.1109/ISCV49265.2020.9204174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Exponentially decaying signals occur in various parts of nature and affect the performance and flexibility of signals. In fact, that drives scientists to invest in a perpetual search for new solutions. To meet this challenge few methods are proposed. In this study, we focused on the use of the Prony Method and Bessel and Butterworth smoothing methods in the LabVIEW environment for estimating the parameters of a sum of real exponential signals in the presence of noise. The performances of the proposed method are illustrated using simulated data, clearly showing the improved performance of the Prony Method and especially with Butterworth filter.\",\"PeriodicalId\":313743,\"journal\":{\"name\":\"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCV49265.2020.9204174\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCV49265.2020.9204174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Smooth Filters for Improving Prony’s Method in Labview Environment
Exponentially decaying signals occur in various parts of nature and affect the performance and flexibility of signals. In fact, that drives scientists to invest in a perpetual search for new solutions. To meet this challenge few methods are proposed. In this study, we focused on the use of the Prony Method and Bessel and Butterworth smoothing methods in the LabVIEW environment for estimating the parameters of a sum of real exponential signals in the presence of noise. The performances of the proposed method are illustrated using simulated data, clearly showing the improved performance of the Prony Method and especially with Butterworth filter.