中文摘要：

稀疏信号的快速优化恢复是压缩感知理论（Compressed Sensing，CS）研究的热点。讨论了参数选取对迭代加权l1范数优化算法恢复效果的影响，并将参数规则化过程引入到算法中，提出了带有参数规则化过程的迭代加权l1范数优化算法。最后通过数值实验，表明改进的算法较大程度地提升了对稀疏信号的恢复能力。

英文摘要：

Rapid recovery of sparse signals is an important issue in compressed sensing.This paper discusses the parameter selection of the signal recovery algorithm via the iterative weighted l1 norm.A regularization strategy is introduced for the iterative weighted l1 norm to improve the stability of the recovery algorithm.Several numerical experiments are carried out to evaluate the improvement of the proposed algorithm.Numerical result shows that the proposed algorithm can obviously improve the accuracy and stability of sparse signal recovery.