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A modified sequential quadratic programming method for sparse signal recovery problems
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DOI：10.1016/j.sigpro.2023.108955.png)
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Abstract
En 中文
We propose a modified sequential quadratic programming method for solving the sparse signal recovery problem. We start by going through the well-known smoothed-l(0) technique and provide a smooth ap-proximation of the objective function. Then, a variant of the sequential quadratic programming method equipped with a new approach for solving subproblems is proposed. We investigate the global con-vergence of the method in detail. In comparison to several well-known algorithms, simulation results demonstrate the promising performance of the proposed method.(c) 2023 Elsevier B.V. All rights reserved.
Keywords:
Sparse signal recovery
Sequential programming method
SL0 approximation
Non-convex optimization
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