Chaotic signal denoising algorithm based on sparse decomposition

doi:10.1088/1674-1056/ab8a3b

中国物理B ›› 2020, Vol. 29 ›› Issue (6): 60505-060505.doi: 10.1088/1674-1056/ab8a3b

• SPECIAL TOPIC—Recent advances in thermoelectric materials and devices • 上一篇下一篇

Chaotic signal denoising algorithm based on sparse decomposition

Jin-Wang Huang(黄锦旺), Shan-Xiang Lv(吕善翔), Zu-Sheng Zhang(张足生), Hua-Qiang Yuan(袁华强)

1 School of Cyberspace Science, Dongguan University of Technology, Dongguan 523808, China;
2 College of Cyber Security, Jinan University, Guangzhou 510632, China

收稿日期:2020-02-27 修回日期:2020-04-10 出版日期:2020-06-05 发布日期:2020-06-05
通讯作者: Hua-Qiang Yuan E-mail:yuanhq@dgut.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 61872083) and the Natural Science Foundation of Guangdong Province, China (Grant Nos. 2017A030310659 and 2019A1515011123).

Chaotic signal denoising algorithm based on sparse decomposition

Jin-Wang Huang(黄锦旺)¹, Shan-Xiang Lv(吕善翔)², Zu-Sheng Zhang(张足生)¹, Hua-Qiang Yuan(袁华强)¹

1 School of Cyberspace Science, Dongguan University of Technology, Dongguan 523808, China;
2 College of Cyber Security, Jinan University, Guangzhou 510632, China

Received:2020-02-27 Revised:2020-04-10 Online:2020-06-05 Published:2020-06-05
Contact: Hua-Qiang Yuan E-mail:yuanhq@dgut.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 61872083) and the Natural Science Foundation of Guangdong Province, China (Grant Nos. 2017A030310659 and 2019A1515011123).

摘要/Abstract

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.

关键词: sparse decomposition, denoising, K-SVD, chaotic signal

Abstract: 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.

Key words: sparse decomposition, denoising, K-SVD, chaotic signal

中图分类号: (Nonlinear dynamics and chaos)

05.45.-a

05.40.Ca (Noise)

黄锦旺, 吕善翔, 张足生, 袁华强. Chaotic signal denoising algorithm based on sparse decomposition[J]. 中国物理B, 2020, 29(6): 60505-060505.

Jin-Wang Huang(黄锦旺), Shan-Xiang Lv(吕善翔), Zu-Sheng Zhang(张足生), Hua-Qiang Yuan(袁华强). Chaotic signal denoising algorithm based on sparse decomposition[J]. Chin. Phys. B, 2020, 29(6): 60505-060505.

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Chaotic signal denoising algorithm based on sparse decomposition

Chaotic signal denoising algorithm based on sparse decomposition

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