{"title":"干扰背景下u滤波器的高斯化函数","authors":"Wang Pingbo, Liu Feng, C. Zhiming, Tang Suofu","doi":"10.1109/ICSAP.2010.77","DOIUrl":null,"url":null,"abstract":"By weakening the bigger and strengthening the smaller, gaussianization can enhance the gaussianity of samples and improve performance of subsequent correlation test. Firstly, an explicit definition on gaussianizing filter and a practical method to evaluate the filtering performance are given. Secondly, based on the probability density function and its derivate, one typical gaussianizing filters, so-called U-filter, are proposed and studied. Instances with lake trial data are illustrated. Finally, two applications, one in spectrum estimation and the other in Rao test, are discussed.","PeriodicalId":244652,"journal":{"name":"2009 International Conference on Wireless Communications & Signal Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"U-filter's gaussianization function for interference background\",\"authors\":\"Wang Pingbo, Liu Feng, C. Zhiming, Tang Suofu\",\"doi\":\"10.1109/ICSAP.2010.77\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By weakening the bigger and strengthening the smaller, gaussianization can enhance the gaussianity of samples and improve performance of subsequent correlation test. Firstly, an explicit definition on gaussianizing filter and a practical method to evaluate the filtering performance are given. Secondly, based on the probability density function and its derivate, one typical gaussianizing filters, so-called U-filter, are proposed and studied. Instances with lake trial data are illustrated. Finally, two applications, one in spectrum estimation and the other in Rao test, are discussed.\",\"PeriodicalId\":244652,\"journal\":{\"name\":\"2009 International Conference on Wireless Communications & Signal Processing\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-02-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Wireless Communications & Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAP.2010.77\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Wireless Communications & Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAP.2010.77","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
U-filter's gaussianization function for interference background
By weakening the bigger and strengthening the smaller, gaussianization can enhance the gaussianity of samples and improve performance of subsequent correlation test. Firstly, an explicit definition on gaussianizing filter and a practical method to evaluate the filtering performance are given. Secondly, based on the probability density function and its derivate, one typical gaussianizing filters, so-called U-filter, are proposed and studied. Instances with lake trial data are illustrated. Finally, two applications, one in spectrum estimation and the other in Rao test, are discussed.