{"title":"有序正交匹配追踪","authors":"Deepak Baby, S. R. Pillai","doi":"10.1109/NCC.2012.6176775","DOIUrl":null,"url":null,"abstract":"Compressed Sensing deals with recovering sparse signals from a relatively small number of linear measurements. Several algorithms exists for data recovery from the compressed measurements, particularly appealing among these is the greedy approach known as Orthogonal Matching Pursuit (OMP). In this paper, we propose a modified OMP based algorithm called Ordered Orthogonal Matching Pursuit (Ordered OMP). Ordered OMP is conceptually simpler and provides an improved performance when compared to OMP.","PeriodicalId":178278,"journal":{"name":"2012 National Conference on Communications (NCC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Ordered Orthogonal Matching Pursuit\",\"authors\":\"Deepak Baby, S. R. Pillai\",\"doi\":\"10.1109/NCC.2012.6176775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compressed Sensing deals with recovering sparse signals from a relatively small number of linear measurements. Several algorithms exists for data recovery from the compressed measurements, particularly appealing among these is the greedy approach known as Orthogonal Matching Pursuit (OMP). In this paper, we propose a modified OMP based algorithm called Ordered Orthogonal Matching Pursuit (Ordered OMP). Ordered OMP is conceptually simpler and provides an improved performance when compared to OMP.\",\"PeriodicalId\":178278,\"journal\":{\"name\":\"2012 National Conference on Communications (NCC)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 National Conference on Communications (NCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCC.2012.6176775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 National Conference on Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2012.6176775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compressed Sensing deals with recovering sparse signals from a relatively small number of linear measurements. Several algorithms exists for data recovery from the compressed measurements, particularly appealing among these is the greedy approach known as Orthogonal Matching Pursuit (OMP). In this paper, we propose a modified OMP based algorithm called Ordered Orthogonal Matching Pursuit (Ordered OMP). Ordered OMP is conceptually simpler and provides an improved performance when compared to OMP.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
