{"title":"一种基于去相关和分块矩阵的快速盲反卷积算法","authors":"Jun-an Yang, Xue-ping He, Yunxiao Jiang","doi":"10.1109/ICNC.2007.21","DOIUrl":null,"url":null,"abstract":"In order to alleviate the shortcomings of most blind deconvolution algorithms, this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix. Althougth the original algorithm proposed in ref (H. Buchner et al., 2003) can overcome the shortcomings of current blind deconvolution algorithms, but it has a constraint that the number of the source signals must be less than that of the channels'. The improved algorithm deletes this constraint by using decorrelation technique. Besides, the improved algorithm raises the separation speed in terms of improving the computing methods of output signals matrix. Simulation results demonstrate the validation and fast separation of the improved algorithm.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Fast Blind Deconvolution Algorithm Using Decorrelation and Block Matrix\",\"authors\":\"Jun-an Yang, Xue-ping He, Yunxiao Jiang\",\"doi\":\"10.1109/ICNC.2007.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to alleviate the shortcomings of most blind deconvolution algorithms, this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix. Althougth the original algorithm proposed in ref (H. Buchner et al., 2003) can overcome the shortcomings of current blind deconvolution algorithms, but it has a constraint that the number of the source signals must be less than that of the channels'. The improved algorithm deletes this constraint by using decorrelation technique. Besides, the improved algorithm raises the separation speed in terms of improving the computing methods of output signals matrix. Simulation results demonstrate the validation and fast separation of the improved algorithm.\",\"PeriodicalId\":250881,\"journal\":{\"name\":\"Third International Conference on Natural Computation (ICNC 2007)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third International Conference on Natural Computation (ICNC 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2007.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Natural Computation (ICNC 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2007.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
针对大多数盲反卷积算法的不足,提出了一种基于去相关技术和宽带分块矩阵的快速盲反卷积改进算法。虽然在ref (H. Buchner et al., 2003)中提出的原始算法可以克服当前盲反卷积算法的缺点,但它有一个约束,即源信号的数量必须小于信道的数量。改进算法利用去相关技术消除该约束。改进后的算法在改进输出信号矩阵的计算方法方面提高了分离速度。仿真结果验证了改进算法的有效性和分离速度。
A Fast Blind Deconvolution Algorithm Using Decorrelation and Block Matrix
In order to alleviate the shortcomings of most blind deconvolution algorithms, this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix. Althougth the original algorithm proposed in ref (H. Buchner et al., 2003) can overcome the shortcomings of current blind deconvolution algorithms, but it has a constraint that the number of the source signals must be less than that of the channels'. The improved algorithm deletes this constraint by using decorrelation technique. Besides, the improved algorithm raises the separation speed in terms of improving the computing methods of output signals matrix. Simulation results demonstrate the validation and fast separation of the improved algorithm.