中文摘要：

NESTA是一种解决压缩感知问题的快速准确一阶优化算法。提出了一种自适应重启方法来提高NESTA算法的收敛速度。新方法自动检测目标函数在优化过程收敛速度减缓的趋势,重置算法的参数,并使算法从当前步骤重新开始运行。实验结果表明该方法能够显著提高经典算法的收敛速度,从而提升算法运行效率。

英文摘要：

NESTA is a fast and accurate first-order optimization algorithm to solve problem of compressed sensing. The paper proposes an adaptive restart method to improve the con- vergence rate of NESTA. As object function decreases slowly in NESTA, this method can cope with it and significantly improve the convergence rate of the algorithm. Making the al- gorithm restart from current step, the adaptive restart strategy automatically detects the slow convergence rate of object function and resets the parameters of the algorithm. Exper- imental results show that the method can significantly improve the convergence rate of the classical algorithm, thereby enhance the efficiency of the algorithm.