{"title":"基于经验模态分解的光纤陀螺测量降噪算法","authors":"K. Brzostowski, J. Swiatek","doi":"10.1109/ICSEng.2017.55","DOIUrl":null,"url":null,"abstract":"The paper presents a new method to signal denoising based on Empirical Mode Decomposition and sparse optimization with application to fiber optical gyroscope measurement. The conventional approaches to signal denoising designed for Empirical Mode Decomposition are partial reconstruction and thresholding. Inspired by the second one, we propose a novel method that extends the performance the conventional methods. Our method based on the concept of sparse optimization. To validate the proposed approach, we test its performance for the real signal acquired from fiber optical gyroscope.","PeriodicalId":202005,"journal":{"name":"2017 25th International Conference on Systems Engineering (ICSEng)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Empirical Mode Decomposition Based Denoising Algorithm for Fibre Optical Gyroscope Measurement\",\"authors\":\"K. Brzostowski, J. Swiatek\",\"doi\":\"10.1109/ICSEng.2017.55\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a new method to signal denoising based on Empirical Mode Decomposition and sparse optimization with application to fiber optical gyroscope measurement. The conventional approaches to signal denoising designed for Empirical Mode Decomposition are partial reconstruction and thresholding. Inspired by the second one, we propose a novel method that extends the performance the conventional methods. Our method based on the concept of sparse optimization. To validate the proposed approach, we test its performance for the real signal acquired from fiber optical gyroscope.\",\"PeriodicalId\":202005,\"journal\":{\"name\":\"2017 25th International Conference on Systems Engineering (ICSEng)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 25th International Conference on Systems Engineering (ICSEng)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSEng.2017.55\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 25th International Conference on Systems Engineering (ICSEng)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEng.2017.55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Empirical Mode Decomposition Based Denoising Algorithm for Fibre Optical Gyroscope Measurement
The paper presents a new method to signal denoising based on Empirical Mode Decomposition and sparse optimization with application to fiber optical gyroscope measurement. The conventional approaches to signal denoising designed for Empirical Mode Decomposition are partial reconstruction and thresholding. Inspired by the second one, we propose a novel method that extends the performance the conventional methods. Our method based on the concept of sparse optimization. To validate the proposed approach, we test its performance for the real signal acquired from fiber optical gyroscope.