摘要
有限等距常数是评价压缩感知测量矩阵的重要参数之一,例如压缩感知精确重构须保证有限等距常数满足一定的条件,因此求出有限等距常数具有重要意义。然而,有限等距数的求解是一个NP难的问题。提出了广义有限等距常数,可以作为有限等距常数的一个下限估计值,并给出了一种广义有限等距常数的估计方法。实验结果表明估计结果稳定,可用于进一步研究有限等距常数在压缩感知中的作用。
Restricted isometry constants（RIC） is one of the most important parameters for compressed sensing（CS） measurement matrices evaluation. For example,RIC should meet some conditions to ensure exact reconstruction of CS. Therefore,it is significant to solve out RIC. However,it is a NP-hard problem to solve out RIC. Generalized RIC（GRIC） is proposed,which can be regarded as a lower limit of RIC. Then,a method of GRIC estimation is given out. The GRIC estimation is stable shown by the result of experiments,and it can be used in advanced studies of RIC＇s impact on CS.
作者
贾彬彬
刘俊莹
JIA Bin-bin;LIU Jun-ying(School of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Key Laboratory of Gansu Advanced Control for Industrial Process,Lanzhou University of Technology,Lanzhou 730050,China;National Demonstration Center for Experimental Electrical and Control Engineering Education,Lanzhou University of Technology,Lanzhou 730050,China)
出处
《信息技术》
2018年第7期86-89,共4页
Information Technology
基金
甘肃省自然科学基金(1610RJYA007
1610RJYA026)
甘肃省工业过程先进控制重点实验室开放课题(XJK201517)
关键词
压缩感知
测量矩阵
有限等距性质
有限等距常数
compressed sensing
measurement matrices
restricted isometry property
restrictedisometry constants
