{"title":"基于经验模态分解去噪方法的统计多速率高分辨率信号重建","authors":"Adem Ukte, Aydin Kizilkaya, M. D. Elbi","doi":"10.1109/AE.2014.7011725","DOIUrl":null,"url":null,"abstract":"High-resolution signal reconstruction from a set of its noisy low-resolution measurements is considered. As an alternative solution to this problem, a method employing the empirical mode decomposition (EMD) based denoising approach is proposed. In the framework of the proposed method, iterative EMD interval-thresholding based denoising procedure is applied to each noisy low-resolution measurement so as to filter the additive white Gaussian noise effect on it. We then synthesize the noise-reduced low-resolution signals to form the high-resolution signal. Unlike the method using the Wiener filter theory for high-resolution signal reconstruction, the proposed method does not require knowledge of any correlation information about the desired high-resolution signal and its low-resolution versions. The validity of the proposed method is demonstrated by an audio signal reconstruction application.","PeriodicalId":149779,"journal":{"name":"2014 International Conference on Applied Electronics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Statistical multirate high-resolution signal reconstruction using the empirical mode decomposition based denoising approach\",\"authors\":\"Adem Ukte, Aydin Kizilkaya, M. D. Elbi\",\"doi\":\"10.1109/AE.2014.7011725\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-resolution signal reconstruction from a set of its noisy low-resolution measurements is considered. As an alternative solution to this problem, a method employing the empirical mode decomposition (EMD) based denoising approach is proposed. In the framework of the proposed method, iterative EMD interval-thresholding based denoising procedure is applied to each noisy low-resolution measurement so as to filter the additive white Gaussian noise effect on it. We then synthesize the noise-reduced low-resolution signals to form the high-resolution signal. Unlike the method using the Wiener filter theory for high-resolution signal reconstruction, the proposed method does not require knowledge of any correlation information about the desired high-resolution signal and its low-resolution versions. The validity of the proposed method is demonstrated by an audio signal reconstruction application.\",\"PeriodicalId\":149779,\"journal\":{\"name\":\"2014 International Conference on Applied Electronics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Applied Electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AE.2014.7011725\",\"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 International Conference on Applied Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AE.2014.7011725","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical multirate high-resolution signal reconstruction using the empirical mode decomposition based denoising approach
High-resolution signal reconstruction from a set of its noisy low-resolution measurements is considered. As an alternative solution to this problem, a method employing the empirical mode decomposition (EMD) based denoising approach is proposed. In the framework of the proposed method, iterative EMD interval-thresholding based denoising procedure is applied to each noisy low-resolution measurement so as to filter the additive white Gaussian noise effect on it. We then synthesize the noise-reduced low-resolution signals to form the high-resolution signal. Unlike the method using the Wiener filter theory for high-resolution signal reconstruction, the proposed method does not require knowledge of any correlation information about the desired high-resolution signal and its low-resolution versions. The validity of the proposed method is demonstrated by an audio signal reconstruction application.