Noise Robust Method for Analytically Solvable Chaotic Signal Reconstruction
Noise Robust Method for Analytically Solvable Chaotic Signal Reconstruction
复制标题
用于解析可解混沌信号重建的噪声鲁棒方法
DOI：
10.1007/s00034-019-01043-y
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Guo Chen
中科院分区：
文献类型：
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作者：
Liu Lidong;Wang Yanan;Li Yi;Feng Xiaoran;Song Huansheng;He Zhili;Guo Chen
针对强噪声条件下解析可解混沌系统（ASCS）的混沌信号重构问题，提出了一种新的重构方法.该方法首先在强噪声条件下对观测信号进行二进制积分，并将积分结果与零值阈值进行比较，得到ASCS的二进制符号。然后，原始信号和另一个ASCS之间的关系是基于所获得的二进制符号序列解析推导。根据推导出的关系式，原始信号可以由另一个ASCS的输出重构，该ASCS由所获得的二进制符号序列进行时间反转。理论上，由于加性白色高斯噪声在每个积分区间的积分结果都趋近于零，因此该方法能够在强噪声条件下重构信号，且误差较小。仿真结果表明，该方法在信噪比为dB的情况下仍能以较小的误差重构原始混沌信号，优于传统方法。
A new chaotic signal reconstruction method for analytically solvable chaotic systems (ASCS) under strong noise condition is proposed in this paper, which solves the problem of unsatisfactory reconstruction performance under strong noise condition. In the proposed method, firstly, binary symbols of ASCS are obtained under strong noise condition by integrating the observed signal over a specific interval of every binary symbol period and comparing integration results with a zero value threshold. Then, the relationship between the original signal and another ASCS is derived analytically based on the obtained binary symbol sequence. According to the derived relationship, the original signal can be reconstructed by the output of another ASCS which is driven by the obtained binary symbol sequence reversed in time. Theoretically, the proposed method can reconstruct signals under strong noise condition with small error since the integration result of additive white Gaussian noise in every integration interval approaches zero. Finally, the proposed method is demonstrated with numerical simulations which show the original chaotic signal can be reconstructed with small error even when the signal-to-noise ratio isdB, and thus the proposed method outperforms conventional methods.