{"title":"LMS自适应算法中系统失配协方差矩阵的性质","authors":"Laura-Maria Dogariu, S. Ciochină, C. Paleologu","doi":"10.1109/iccomm.2018.8484800","DOIUrl":null,"url":null,"abstract":"Ahstract-The system mismatch covariance matrix is of major interest in some of the optimization approaches of the least-mean-square type adaptive algorithms. Some examples are the ones based on the Kalman filtering theory, or the variable step-size algorithms based on the minimization of the mean square system mismatch. All of them require information about this specific matrix. The usual assumption is to approximate this matrix with a scaled unity one. This paper analyzes the validity conditions of this assumption. Simulation results support the theoretical findings.","PeriodicalId":158890,"journal":{"name":"2018 International Conference on Communications (COMM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the Properties of the System Mismatch Covariance Matrix in the LMS Adaptive Algorithm\",\"authors\":\"Laura-Maria Dogariu, S. Ciochină, C. Paleologu\",\"doi\":\"10.1109/iccomm.2018.8484800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ahstract-The system mismatch covariance matrix is of major interest in some of the optimization approaches of the least-mean-square type adaptive algorithms. Some examples are the ones based on the Kalman filtering theory, or the variable step-size algorithms based on the minimization of the mean square system mismatch. All of them require information about this specific matrix. The usual assumption is to approximate this matrix with a scaled unity one. This paper analyzes the validity conditions of this assumption. Simulation results support the theoretical findings.\",\"PeriodicalId\":158890,\"journal\":{\"name\":\"2018 International Conference on Communications (COMM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Communications (COMM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iccomm.2018.8484800\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Communications (COMM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iccomm.2018.8484800","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the Properties of the System Mismatch Covariance Matrix in the LMS Adaptive Algorithm
Ahstract-The system mismatch covariance matrix is of major interest in some of the optimization approaches of the least-mean-square type adaptive algorithms. Some examples are the ones based on the Kalman filtering theory, or the variable step-size algorithms based on the minimization of the mean square system mismatch. All of them require information about this specific matrix. The usual assumption is to approximate this matrix with a scaled unity one. This paper analyzes the validity conditions of this assumption. Simulation results support the theoretical findings.