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- W4312156716 abstract "This paper is concerned with the problem of line spectral estimation. Reweighted atomic norm minimization based on Toeplitz model (RAM-T) is a promising approach that promotes sparsity and enhances resolution as compared to atomic norm minimization (ANM) by generalizing the atomic norm with a new sparsity metric. To address the slow convergence issue of RAM-T, in this paper, we propose a reweighted atomic norm minimization approach by exploiting the recently proposed Hankel–Toeplitz model, which achieves a better performance and converges faster than RAM-T. Furthermore, we reveal the connection between reweighted atomic norm minimization based on Hankel–Toeplitz model (RAM-HT) and RAM-T and give sufficient conditions for successful signal recovery of the first iteration of RAM-HT. Numerical experiments demonstrate the superior performance of our proposed approach." @default.
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- W4312156716 date "2023-05-01" @default.
- W4312156716 modified "2023-10-15" @default.
- W4312156716 title "New reweighted atomic norm minimization approach for line spectral estimation" @default.
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- W4312156716 doi "https://doi.org/10.1016/j.sigpro.2022.108897" @default.
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