{"title":"Golay meets Hadamard: Golay-paired Hadamard matrices for fast compressed sensing","authors":"Lu Gan, Kezhi Li, Cong Ling","doi":"10.1109/ITW.2012.6404755","DOIUrl":null,"url":null,"abstract":"This paper introduces Golay-paired Hadamard matrices for fast compressed sensing of sparse signals in the time or spectral domain. These sampling operators feature low-memory requirement, hardware-friendly implementation and fast computation in reconstruction. We show that they require a nearly optimal number of measurements for faithful reconstruction of a sparse signal in the time or frequency domain. Simulation results demonstrate that the proposed sensing matrices offer a reconstruction performance similar to that of fully random matrices.","PeriodicalId":325771,"journal":{"name":"2012 IEEE Information Theory Workshop","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Information Theory Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITW.2012.6404755","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
This paper introduces Golay-paired Hadamard matrices for fast compressed sensing of sparse signals in the time or spectral domain. These sampling operators feature low-memory requirement, hardware-friendly implementation and fast computation in reconstruction. We show that they require a nearly optimal number of measurements for faithful reconstruction of a sparse signal in the time or frequency domain. Simulation results demonstrate that the proposed sensing matrices offer a reconstruction performance similar to that of fully random matrices.
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