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A Generalized Elastic Net Regularization with Smoothed <i>l</i><sub>0</sub> Penalty
Department of Mathematics, College of Science, Shanghai University, Shanghai, China
Department of Mathematics, College of Science, Shanghai University, Shanghai, China
- 1 Department of Mathematics, College of Science, Shanghai University, Shanghai, China
- 2 Department of Mathematics, College of Science, Shanghai University, Shanghai, China
Advances in Pure Mathematics·Volume 07 (2017)·Pages 66–74·Published 23 January 2017·DOI10.4236/apm.2017.71006
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Abstract
This paper presents an accurate and efficient algorithm for solving the generalized elastic net regularization problem with smoothed l 0 penalty for recovering sparse vector. Finding the optimal solution to the unconstrained l 0 minimization problem in the recovery of compressive sensed signals is an NP-hard problem. We proposed an iterative algorithm to solve this problem. We then prove that the algorithm is convergent based on algebraic methods. The numerical result shows the efficiency and the accuracy of the algorithm.
KeywordsSparse VectorCompressed SenseElastic Net Regularization<i>l</i><sub>0</sub>Minimization
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