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Low Rank Vectorized Hankel Lift for Matrix Recovery via Fast Iterative Hard Thresholding

by   Zengying Zhu, et al.
FUDAN University

We propose a VHL-FIHT algorithm for matrix recovery in blind super-resolution problems in a nonconvex schema. Under certain assumptions, we show that VHL-FIHT converges to the ground truth with linear convergence rate. Numerical experiments are conducted to validate the linear convergence and effectiveness of the proposed approach.


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