National Natural Science Foundation of China (No.61671338, No.61473213, No.51774219);Fund of Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System (No.znxx2018QN04, No.znxx2018QN01)
WANG Wen-bo, JIN Yun-yu, WANG Bin, et al. Chaotic Signal De-noising Based on Adaptive Threshold Synchrosqueezed Wavelet Transform[J]. Acta Electronica Sinica, 2018, 46(7): 1652-1657.
DOI:
WANG Wen-bo, JIN Yun-yu, WANG Bin, et al. Chaotic Signal De-noising Based on Adaptive Threshold Synchrosqueezed Wavelet Transform[J]. Acta Electronica Sinica, 2018, 46(7): 1652-1657. DOI: 10.3969/j.issn.0372-2112.2018.07.016.
Chaotic Signal De-noising Based on Adaptive Threshold Synchrosqueezed Wavelet Transform
For the lack of the single threshold denoising method of synchrosqueezed wavelet transform(SST)
an improved denoising method for chaotic signal is proposed based on SST hierarchical threshold.Firstly
according to the distribution models of SST decomposition coefficients of the signal and the noise
the formula of mean square error of SST chaotic signal denoising is derived
which contains the threshold coefficients of amplitude.Then
the optimal threshold coefficients of amplitude is calculated based on the minimum mean square error criterion.Finally
the optimal hierarchical thresholds of SST chaotic denoising is determined according to the optimal threshold coefficients and the standard deviation of the noise.In the experiments
the denoising performance of the proposed method is tested by using the simulated chaotic signals and the measured monthly sunspot signals.The experimental results show that the proposed method can filter the noise of chaotic signal better
and the chaotic properties of the originals can be largely recovered.The proposed method can obtain better performance in the chaotic signal denoising than the classical wavelet transform threshold method and the EEMD denoising method.