CAJ | 학술논문

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l_1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l_1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.
희소신호적쾌속우화회복시압축감지이론(Compressed Sensing,CS)연구적열점.토론료삼수선취대질대가권l_1범수우화산법회복효과적영향,병장삼수규칙화과정인입도산법중,제출료대유삼수규칙화과정적질대가권l_1범수우화산법.최후통과수치실험,표명개진적산법교대정도지제승료대희소신호적회복능력.
Rapid recovery of sparse signals is an important issue in compressed sensing.This paper discusses the parameter se-lection of the signal recovery algorithm via the iterative weighted l_1 norm.A regularization strategy is introduced for the iterative weighted l_1 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.