Chaotic Signal Denoising Based on Hierarchical Threshold Synchrosqueezed Wavelet Transform

1st International Global on Renewable Energy and Development

Wang, Wen-Bo^1 ; Jing, Yun-Yu^1 ; Zhao, Yan-Chao^1 ; Zhang, Lian-Hua^2 ; Wang, Xiang-Li^3

College of Science, Wuhan University of Science and Technology, Wuhan

430065, China^1

School of Literature Law and Economics, Wuhan University of Science and Technology, Wuhan

430065, China^2

School of Computer Science and Technology, Wuhan University of Technology, Wuhan

430070, China^3

关键词: Chaotic characteristics;    Denoising methods;    Minimum mean square errors;    Optimal estimations;    Risk estimation;    Synchrosque-ezed wavelet transforms;    Threshold functions;    Threshold process;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/100/1/012163/pdf
DOI  :  10.1088/1755-1315/100/1/012163

来源: IOP

【 摘 要 】

In order to overcoming the shortcoming of single threshold synchrosqueezed wavelet transform(SWT) denoising method, an adaptive hierarchical threshold SWT chaotic signal denoising method is proposed. Firstly, a new SWT threshold function is constructed based on Stein unbiased risk estimation, which is two order continuous derivable. Then, by using of the new threshold function, a threshold process based on the minimum mean square error was implemented, and the optimal estimation value of each layer threshold in SWT chaotic denoising is obtained. The experimental results of the simulating chaotic signal and measured sunspot signals show that, the proposed method can filter the noise of chaotic signal well, and the intrinsic chaotic characteristic of the original signal can be recovered very well. Compared with the EEMD denoising method and the single threshold SWT denoising method, the proposed method can obtain better denoising result for the chaotic signal.