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Sparse free deconvolution under unknown noise level via eigenmatrix
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DOI：10.1016/j.acha.2025.101802.png)
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Abstract
En 中文
This note considers the spectral estimation problems of sparse spectral measures under unknown noise levels. The main technical tool is the eigenmatrix method for solving unstructured sparse recovery problems. When the noise level is determined, the free deconvolution reduces the problem to an unstructured sparse recovery problem to which the eigenmatrix method can be applied. To determine the unknown noise level, we propose an optimization problem based on the singular values of an intermediate matrix of the eigenmatrix method. Numerical results are provided for both the additive and multiplicative free deconvolutions.
Keywords:
sparse spectral measures
eigenmatrix method
unstructured sparse recovery
noise level estimation
free deconvolution
Journal
IF:
3.2
Papers:
95
Citations:
3.9K
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