{"title":"鲁棒权约束解相关归一化最大Versoria算法","authors":"Zhao Zhang, Sheng Zhang, Jiashu Zhang","doi":"10.1109/IWSDA46143.2019.8966128","DOIUrl":null,"url":null,"abstract":"A robust weight-constraint decorrelation normalized maximum versoria algorithm is proposed in this paper. The proposed algorithm is designed by maximizing the normalized versoria cost function of the decorrelation error, and thus is robust against the impulsive noise and exhibits fast convergence in the case of highly correlated signals. The stability and computational complexity also be analyzed. Finally, simulation results demonstrate that the proposed algorithm achieves faster convergence speed than the MVC algorithm for colored input signal under the impulsive noise environment.","PeriodicalId":326214,"journal":{"name":"2019 Ninth International Workshop on Signal Design and its Applications in Communications (IWSDA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Robust Weight-Constraint Decorrelation Normalized Maximum Versoria Algorithm\",\"authors\":\"Zhao Zhang, Sheng Zhang, Jiashu Zhang\",\"doi\":\"10.1109/IWSDA46143.2019.8966128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A robust weight-constraint decorrelation normalized maximum versoria algorithm is proposed in this paper. The proposed algorithm is designed by maximizing the normalized versoria cost function of the decorrelation error, and thus is robust against the impulsive noise and exhibits fast convergence in the case of highly correlated signals. The stability and computational complexity also be analyzed. Finally, simulation results demonstrate that the proposed algorithm achieves faster convergence speed than the MVC algorithm for colored input signal under the impulsive noise environment.\",\"PeriodicalId\":326214,\"journal\":{\"name\":\"2019 Ninth International Workshop on Signal Design and its Applications in Communications (IWSDA)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Ninth International Workshop on Signal Design and its Applications in Communications (IWSDA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWSDA46143.2019.8966128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Ninth International Workshop on Signal Design and its Applications in Communications (IWSDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWSDA46143.2019.8966128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust Weight-Constraint Decorrelation Normalized Maximum Versoria Algorithm
A robust weight-constraint decorrelation normalized maximum versoria algorithm is proposed in this paper. The proposed algorithm is designed by maximizing the normalized versoria cost function of the decorrelation error, and thus is robust against the impulsive noise and exhibits fast convergence in the case of highly correlated signals. The stability and computational complexity also be analyzed. Finally, simulation results demonstrate that the proposed algorithm achieves faster convergence speed than the MVC algorithm for colored input signal under the impulsive noise environment.
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