In this paper, we propose a novel sparse recovery method based on the generalized error function. Both the theoretical analysis and the practical algorithms are presented. Numerical experiments are conducted to demonstrate the advantageous performance of the proposed approach over the state-of-the-art sparse recovery methods. Its practical application in magnetic resonance imaging (MRI) reconstruction is studied as well.

翻译：在本文中,我们基于普遍误差功能提出了一种新的稀有回收方法。 提出了理论分析和实际算法。 进行了数值实验,以证明拟议方法相对于最先进的稀有恢复方法的有利性。 也研究了其在磁共振成像(MRI)重建中的实际应用。