{"title":"Parameter estimation of non-Gaussian probability density of one-dimensional signals and interferences by iterative method of maximum likelihood","authors":"E. Ibatoulline","doi":"10.1109/ICSMC2.2003.1428266","DOIUrl":null,"url":null,"abstract":"In this report, the use of iterative method of maximum likelihood is considered, which common algorithm was circumscribed earlier, for the parameter estimation of the non-Gaussian probability density of one-dimensional signals and interferences. The formulas for determination of means and variances maximizing the logarithms of private likelihood functions are obtained. The simulation is carried out and the numerical results indicating good the capabilities of method are obtained","PeriodicalId":272545,"journal":{"name":"2003 IEEE International Symposium on Electromagnetic Compatibility, 2003. EMC '03.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 IEEE International Symposium on Electromagnetic Compatibility, 2003. EMC '03.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSMC2.2003.1428266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this report, the use of iterative method of maximum likelihood is considered, which common algorithm was circumscribed earlier, for the parameter estimation of the non-Gaussian probability density of one-dimensional signals and interferences. The formulas for determination of means and variances maximizing the logarithms of private likelihood functions are obtained. The simulation is carried out and the numerical results indicating good the capabilities of method are obtained
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
