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4. Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers

Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers

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IEEE ICASSP 2020 Virtual Conference May 2020

We study how to estimate a nearly low-rank Toeplitz covariance matrix T from compressed measurements. Recent work of Qiao and Pal addresses this problem by combining sparse rulers (sparse linear arrays) with frequency finding (sparse Fourier transform) al

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Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers

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We study how to estimate a nearly low-rank Toeplitz covariance matrix T from compressed measurements. Recent work of Qiao and Pal addresses this problem by combining sparse rulers (sparse linear arrays) with frequency finding (sparse Fourier transform) al