{"title":"学生滤波器对信号进行时频分析与合成","authors":"Bogdan Semenov, I. Shelevytsky","doi":"10.1109/SPS.2015.7168293","DOIUrl":null,"url":null,"abstract":"Non-linear filter with studentized coefficients of time-frequency decomposition and signal reconstruction is described. The main feature of time-frequency decomposition is least squares estimation of spline fragments of different scales. Filter performs selection of statistically significant components of time-frequency decomposition taking into account local variance of residuals. The main advantage is that it filters fragments of white noise from the signal.","PeriodicalId":193902,"journal":{"name":"2015 Signal Processing Symposium (SPSympo)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Studentized filter of time-frequency analysis and synthesis of the signals\",\"authors\":\"Bogdan Semenov, I. Shelevytsky\",\"doi\":\"10.1109/SPS.2015.7168293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Non-linear filter with studentized coefficients of time-frequency decomposition and signal reconstruction is described. The main feature of time-frequency decomposition is least squares estimation of spline fragments of different scales. Filter performs selection of statistically significant components of time-frequency decomposition taking into account local variance of residuals. The main advantage is that it filters fragments of white noise from the signal.\",\"PeriodicalId\":193902,\"journal\":{\"name\":\"2015 Signal Processing Symposium (SPSympo)\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Signal Processing Symposium (SPSympo)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPS.2015.7168293\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing Symposium (SPSympo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPS.2015.7168293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Studentized filter of time-frequency analysis and synthesis of the signals
Non-linear filter with studentized coefficients of time-frequency decomposition and signal reconstruction is described. The main feature of time-frequency decomposition is least squares estimation of spline fragments of different scales. Filter performs selection of statistically significant components of time-frequency decomposition taking into account local variance of residuals. The main advantage is that it filters fragments of white noise from the signal.