{"title":"Fast basis selection methods","authors":"S. Cotter, M. Murthi, B. Rao","doi":"10.1109/ACSSC.1997.679149","DOIUrl":null,"url":null,"abstract":"In this paper three methods of basis selection are considered: basic matching pursuit (BMP), order recursive matching pursuit (ORMP) and modified matching pursuit (MMP). These algorithms are briefly described and particular attention is paid, in the formulation of these algorithms, to the computation required. Fast versions of the algorithms are developed. The algorithms are evaluated in terms of their ability to produce a sparse solution and also in terms of their computational complexity and the storage necessary to implement them. Complexity-wise, BMP and MMP are shown to be comparable while ORMP is the most complex. In terms of their ability to select basis vectors, ORMP was the best followed by MMP and then BMP.","PeriodicalId":240431,"journal":{"name":"Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.1997.679149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
In this paper three methods of basis selection are considered: basic matching pursuit (BMP), order recursive matching pursuit (ORMP) and modified matching pursuit (MMP). These algorithms are briefly described and particular attention is paid, in the formulation of these algorithms, to the computation required. Fast versions of the algorithms are developed. The algorithms are evaluated in terms of their ability to produce a sparse solution and also in terms of their computational complexity and the storage necessary to implement them. Complexity-wise, BMP and MMP are shown to be comparable while ORMP is the most complex. In terms of their ability to select basis vectors, ORMP was the best followed by MMP and then BMP.