{"title":"非平稳离散输入线性系统的盲反卷积","authors":"T.-H. Li","doi":"10.1109/HOST.1993.264576","DOIUrl":null,"url":null,"abstract":"A method is proposed for blind deconvolution (equalization) of communication channels when their input signals are real- or complex-valued multilevel random sequences. The gist of the method is to apply a linear filter (equalizer) to the observed signal and to adjust it until a multilevel sequence is obtained from the output. It is shown that the problem can be solved with only scale/rotation and shift ambiguities. A cost function is proposed so that any minimizer of the function provides a solution to the problem. When the channel is parametric, a procedure is presented for the consistent estimation of the channel parameters. All these results are obtained for nonminimum phase linear systems without assuming the stationarity of the signal.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Blind deconvolution of linear systems with nonstationary discrete inputs\",\"authors\":\"T.-H. Li\",\"doi\":\"10.1109/HOST.1993.264576\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method is proposed for blind deconvolution (equalization) of communication channels when their input signals are real- or complex-valued multilevel random sequences. The gist of the method is to apply a linear filter (equalizer) to the observed signal and to adjust it until a multilevel sequence is obtained from the output. It is shown that the problem can be solved with only scale/rotation and shift ambiguities. A cost function is proposed so that any minimizer of the function provides a solution to the problem. When the channel is parametric, a procedure is presented for the consistent estimation of the channel parameters. All these results are obtained for nonminimum phase linear systems without assuming the stationarity of the signal.<<ETX>>\",\"PeriodicalId\":439030,\"journal\":{\"name\":\"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1993.264576\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1993.264576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind deconvolution of linear systems with nonstationary discrete inputs
A method is proposed for blind deconvolution (equalization) of communication channels when their input signals are real- or complex-valued multilevel random sequences. The gist of the method is to apply a linear filter (equalizer) to the observed signal and to adjust it until a multilevel sequence is obtained from the output. It is shown that the problem can be solved with only scale/rotation and shift ambiguities. A cost function is proposed so that any minimizer of the function provides a solution to the problem. When the channel is parametric, a procedure is presented for the consistent estimation of the channel parameters. All these results are obtained for nonminimum phase linear systems without assuming the stationarity of the signal.<>