Author(s)

Sisu Li, Wanzhou Ye

Department of Mathematics, College of Science, Shanghai University, Shanghai, China.

This paper presents an accurate and efficient algorithm for solving the generalized elastic net regularization problem with smoothed l₀ penalty for recovering sparse vector. Finding the optimal solution to the unconstrained l₀ 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.

Sparse Vector, Compressed Sense, Elastic Net Regularization, l₀ Minimization

Li, S. and Ye, W. (2017) A Generalized Elastic Net Regularization with Smoothed l₀ Penalty. Advances in Pure Mathematics, 7, 66-74. doi: 10.4236/apm.2017.71006.