{"title":"EMP信号测量系统的自适应小波去噪方法","authors":"Shi Lihua, Chen Bin, Zhou Binhua, Gao Cheng","doi":"10.1109/CEEM.2000.853917","DOIUrl":null,"url":null,"abstract":"An adaptive wavelet denoising method is proposed to eliminate the noise induced by the measuring system of EMP signals. This method employs a threshold-searching strategy to select an optimal denoising threshold for a given system. Wavelet decomposition and reconstruction are combined with neural network nonlinear threshold-filtering units in the new denoising algorithm. Based on a group of training signal, the denoising threshold can be learned adaptively. The training algorithm and application examples are given in this paper.","PeriodicalId":153945,"journal":{"name":"Proceedings. Asia-Pacific Conference on Environmental Electromagnetics. CEEM'2000 (IEEE Cat. No.00EX402)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An adaptive wavelet denoising method for the measuring system of EMP signals\",\"authors\":\"Shi Lihua, Chen Bin, Zhou Binhua, Gao Cheng\",\"doi\":\"10.1109/CEEM.2000.853917\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An adaptive wavelet denoising method is proposed to eliminate the noise induced by the measuring system of EMP signals. This method employs a threshold-searching strategy to select an optimal denoising threshold for a given system. Wavelet decomposition and reconstruction are combined with neural network nonlinear threshold-filtering units in the new denoising algorithm. Based on a group of training signal, the denoising threshold can be learned adaptively. The training algorithm and application examples are given in this paper.\",\"PeriodicalId\":153945,\"journal\":{\"name\":\"Proceedings. Asia-Pacific Conference on Environmental Electromagnetics. CEEM'2000 (IEEE Cat. No.00EX402)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Asia-Pacific Conference on Environmental Electromagnetics. CEEM'2000 (IEEE Cat. No.00EX402)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEEM.2000.853917\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Asia-Pacific Conference on Environmental Electromagnetics. CEEM'2000 (IEEE Cat. No.00EX402)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEEM.2000.853917","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An adaptive wavelet denoising method for the measuring system of EMP signals
An adaptive wavelet denoising method is proposed to eliminate the noise induced by the measuring system of EMP signals. This method employs a threshold-searching strategy to select an optimal denoising threshold for a given system. Wavelet decomposition and reconstruction are combined with neural network nonlinear threshold-filtering units in the new denoising algorithm. Based on a group of training signal, the denoising threshold can be learned adaptively. The training algorithm and application examples are given in this paper.