摘要
压缩感知中测量矩阵的零空间特性可以确保重建稀疏信号.在l_(1)-l_(2)最小化问题模型下,文章利用测量矩阵的零空间特性,根据已知信号的不同支撑信息,得到了相应的充分条件.这些条件给出了测量矩阵的限制等距性和信号恢复之间的紧密关系,且获得的结论在理论上优于现有的文献结果.
The null space property of the measurement matrix in compressed sensing can ensure the reconstruction of sparse signals.In the l_(1)-l_(2) minimization model,sufficient conditions are obtained according to the different supporting information of known signals by using the null space property of measurement matrix.These conditions give the close relationship between the restricted isometry of the measurement matrix and signal recovery,and the conclusions obtained are better than the existing literature results in theory.
作者
武思琪
宋儒瑛
WU Siqi;SONG Ruying(School of Mathematics and Statistics,Taiyuan Normal University,Jinzhong 030619,China)
出处
《太原师范学院学报（自然科学版）》
2022年第4期16-21,共6页
Journal of Taiyuan Normal University:Natural Science Edition
