Sparse recovery in probability via lq-minimization with Weibull random matrices for 0

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摘要 AlthoughGaussianrandommatricesplayanimportantroleofmeasurementmatricesincompressedsensing,onehopesthatthereexistotherrandommatriceswhichcanalsobeusedtoserveasthemeasurementmatrices.Hence,Weibullrandommatricesinduceextensiveinterest.Inthispaper,wefirstproposethel2,qrobustnullspacepropertythatcanweakentheD-RIP,andshowthatWeibullrandommatricessatisfythel2,qrobustnullspacepropertywithhighprobability.Besides,weprovethatWeibullrandommatricesalsopossessthelqquotientpropertywithhighprobability.Finally,withthecombinationoftheabovementionedproperties,wegivetwoimportantapproximationcharacteristicsofthesolutionstothelq-minimizationwithWeibullrandommatrices,oneisonthestabilityestimatewhenthemeasurementnoisee∈Rnneedsapriori‖e‖2≤,theotherisontherobustnessestimatewithoutneedingtoestimatetheboundof‖e‖2.TheresultsindicatethattheperformanceofWeibullrandommatricesissimilartothatofGaussianrandommatricesinsparserecovery.
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出版日期 2018年01月11日(中国期刊网平台首次上网日期,不代表论文的发表时间)
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