{"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.
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快速基选择方法
本文考虑了基本匹配追踪(BMP)、顺序递归匹配追踪(ORMP)和改进匹配追踪(MMP)三种基本匹配追踪方法。对这些算法进行了简要描述,并在这些算法的制定中特别注意所需的计算。开发了快速版本的算法。这些算法是根据它们产生稀疏解的能力以及它们的计算复杂性和实现它们所需的存储来评估的。在复杂性方面,BMP和MMP具有可比性,而ORMP最为复杂。在选择基向量的能力方面,ORMP最好,其次是MMP,然后是BMP。
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