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Chaotic signal denoising algorithm based on sparse decomposition*
被引:5
作者:
Huang, Jin-Wang
[1
]
Lv, Shan-Xiang
[2
]
Zhang, Zu-Sheng
[1
]
Yuan, Hua-Qiang
[1
]
机构:
[1] Dongguan Univ Technol, Sch Cyberspace Sci, Dongguan 523808, Peoples R China
[2] Jinan Univ, Coll Cyber Secur, Guangzhou 510632, Peoples R China
基金:
中国国家自然科学基金;
关键词:
sparse decomposition;
denoising;
K-SVD;
chaotic signal;
ORTHOGONAL MATCHING PURSUIT;
OVERCOMPLETE REPRESENTATIONS;
NOISE ESTIMATION;
STABLE RECOVERY;
D O I:
10.1088/1674-1056/ab8a3b
中图分类号:
O4 [物理学];
学科分类号:
0702 ;
摘要:
Denoising of chaotic signal is a challenge work due to its wide-band and noise-like characteristics. The algorithm should make the denoised signal have a high signal to noise ratio and retain the chaotic characteristics. We propose a denoising method of chaotic signals based on sparse decomposition and K-singular value decomposition (K-SVD) optimization. The observed signal is divided into segments and decomposed sparsely. The over-complete atomic library is constructed according to the differential equation of chaotic signals. The orthogonal matching pursuit algorithm is used to search the optimal matching atom. The atoms and coefficients are further processed to obtain the globally optimal atoms and coefficients by K-SVD. The simulation results show that the denoised signals have a higher signal to noise ratio and better preserve the chaotic characteristics.
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页数:6
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