Construction of Measurement Matrix in Compressive Sensing Based on Composite Chaotic Mapping

被引：0
|
作者：
Zhou W. [1 ]
Jing B. [1 ]
Zhang H. [2 ]
Huang Y.-F. [1 ]
Li J. [1 ]
机构：
[1] School of Aeronautic & Astronautic Engineering, Air Force Engineering University, Xi'an, 710038, Shaanxi
[2] Beijing Research Institute of Mechanical and Electrical Engineering, Beijing
来源：
| 2017年 / Chinese Institute of Electronics卷 / 45期
关键词：
Chaotic mapping; Compressive sensing (CS); Measurement matrix; Restricted isometry property;
D O I：
10.3969/j.issn.0372-2112.2017.09.018
中图分类号：
学科分类号：
摘要：
Aiming at the difficult in hardware realization of random measurement matrix, we construct a deterministic measurement matrix based on composite chaotic mapping. The composite chaotic mapping that based on Tent mapping and Logistic mapping, has stronger randomicity and initial value sensitivity. Sampled the composite chaotic mapping sequence with large distance, and then do linear transformation to the sampling sequence. Finally, we construct the measurement matrix with the linear transformation result. We prove that the measurement matrix elements have enough statistically independent, and the measurement matrix can satisfies restricted isometry property (RIP) with large probability. The simulation result shows that our matrix has the similar performance to Gaussian random matrix, and better than Toeplitz deterministic measurement matrix and Logistic deterministic measurement matrix. © 2017, Chinese Institute of Electronics. All right reserved.
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页码：2177 / 2183
页数：6
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