{"title":"基于小波的线性测量递归重构算法","authors":"O. Arikan","doi":"10.1109/TFSA.1996.546679","DOIUrl":null,"url":null,"abstract":"A recursive algorithm is proposed to obtain an efficient regularized least squares solution to large linear system of equations which arises in many physical measurement models. The algorithm recursively updates the solution in an increasingly larger dimensional subspace whose basis vectors are chosen as a subset of a complete wavelet basis. Robust criterions on how to chose the basis vectors at each iteration, and when to stop the iterations are given.","PeriodicalId":415923,"journal":{"name":"Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A wavelet based recursive reconstruction algorithm for linear measurements\",\"authors\":\"O. Arikan\",\"doi\":\"10.1109/TFSA.1996.546679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A recursive algorithm is proposed to obtain an efficient regularized least squares solution to large linear system of equations which arises in many physical measurement models. The algorithm recursively updates the solution in an increasingly larger dimensional subspace whose basis vectors are chosen as a subset of a complete wavelet basis. Robust criterions on how to chose the basis vectors at each iteration, and when to stop the iterations are given.\",\"PeriodicalId\":415923,\"journal\":{\"name\":\"Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TFSA.1996.546679\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TFSA.1996.546679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A wavelet based recursive reconstruction algorithm for linear measurements
A recursive algorithm is proposed to obtain an efficient regularized least squares solution to large linear system of equations which arises in many physical measurement models. The algorithm recursively updates the solution in an increasingly larger dimensional subspace whose basis vectors are chosen as a subset of a complete wavelet basis. Robust criterions on how to chose the basis vectors at each iteration, and when to stop the iterations are given.