Extreme Compressive Sampling for Covariance Estimation
IEEE Transactions on Information Theory(2018)
摘要
This paper studies the problem of estimating the covariance of a collection of vectors using only highly compressed measurements of each vector. An estimator based on back-projections of these compressive samples is proposed and analyzed. A distribution-free analysis shows that by observing just a single linear measurement of each vector, one can consistently estimate the covariance matrix, in bot...
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关键词
Estimation,Covariance matrices,Sociology,Principal component analysis,Random variables,Task analysis
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