A Compressed Sensing Framework of Frequency-Sparse Signals through Chaotic Systems
A Compressed Sensing Framework of Frequency-Sparse Signals through Chaotic Systems
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DOI：
10.1142/s0218127412501519
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发表时间：
2011-12
期刊：
影响因子：
--
通讯作者：
Zhong Liu;Shengyao Chen;Feng Xi
中科院分区：
文献类型：
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作者：
Zhong Liu;Shengyao Chen;Feng Xi
提出了一种用于混沌动力系统频率稀疏信号捕获与重构的压缩感知框架。该稀疏信号作为离散混沌系统的激励项，通过对系统输出进行下采样得到压缩量测。重构是通过脉冲混沌同步原理估计激励系数来实现的。利用L1范数正则化的非线性最小二乘法进行估计。建议的框架易于实现，并创建了安全的测量。以Henon映射为例，说明了该方法的原理和性能。
This paper proposes a compressed sensing (CS) framework for the acquisition and reconstruction of frequency-sparse signals with chaotic dynamical systems. The sparse signal acts as an excitation term of a discrete-time chaotic system and the compressed measurement is obtained by downsampling the system output. The reconstruction is realized through the estimation of the excitation coefficients with the principle of impulsive chaos synchronization. The l1-norm regularized nonlinear least squares is used to find the estimation. The proposed framework is easily implementable and creates secure measurements. The Henon map is used as an example to illustrate the principle and the performance.