{"title":"盲均衡通过线性约束最小方差处理","authors":"L. Fertig, J. McClellan","doi":"10.1109/ACSSC.1998.751574","DOIUrl":null,"url":null,"abstract":"A new cost function and a new adaptive structure for blind equalization of communications systems with FIR filters are proposed. It is first shown that the cost function of a previously proposed blind equalization algorithm can be expressed in a similar manner to that of the linearly constrained minimum variance (LCMV) problem (which arises in array processing). This new viewpoint permits a new understanding of the convergence behavior of the previously published technique, as well as the development of new approaches to blind equalization. In particular, a new \"RLS-like\" algorithm is developed that exhibits a convergence rate much faster than previously published algorithms of its class, with a modest increase in computational complexity.","PeriodicalId":393743,"journal":{"name":"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Blind equalization via linearly constrained minimum variance processing\",\"authors\":\"L. Fertig, J. McClellan\",\"doi\":\"10.1109/ACSSC.1998.751574\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new cost function and a new adaptive structure for blind equalization of communications systems with FIR filters are proposed. It is first shown that the cost function of a previously proposed blind equalization algorithm can be expressed in a similar manner to that of the linearly constrained minimum variance (LCMV) problem (which arises in array processing). This new viewpoint permits a new understanding of the convergence behavior of the previously published technique, as well as the development of new approaches to blind equalization. In particular, a new \\\"RLS-like\\\" algorithm is developed that exhibits a convergence rate much faster than previously published algorithms of its class, with a modest increase in computational complexity.\",\"PeriodicalId\":393743,\"journal\":{\"name\":\"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.1998.751574\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.1998.751574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind equalization via linearly constrained minimum variance processing
A new cost function and a new adaptive structure for blind equalization of communications systems with FIR filters are proposed. It is first shown that the cost function of a previously proposed blind equalization algorithm can be expressed in a similar manner to that of the linearly constrained minimum variance (LCMV) problem (which arises in array processing). This new viewpoint permits a new understanding of the convergence behavior of the previously published technique, as well as the development of new approaches to blind equalization. In particular, a new "RLS-like" algorithm is developed that exhibits a convergence rate much faster than previously published algorithms of its class, with a modest increase in computational complexity.