[1]SINHA S, POUTH P S, ANNO P D, et al. Spectral Decomposition of Seismic Data with Continuous-wavelet Transforms [J]. Geophysics, 2005, 70(6):19-25.
[2]DAUBECHIES I , LU Jianfeng, WU H T . Synchrosqueezed Wavelet Transforms:an Empirical Mode Decomposition-like Tool [J]. Applied and Computational Harmonic Analysis, 2011, 30:243-261.
[3]LI Chuan, LIANG Ming. Time-frequency Signal Analysis for Gearbox Fault Diagnosis Using a Generalized Synchrosqueezing Transform [J]. Mechanical Systems and Signal Processing, 2012, 26(1):205-217.
[4]GAURAV T, EUGENE B, NEVEN S, et al. The Synchrosqueezing Algorithm for Time-varying Spectral Analysis: Robustness Properties and New Paleoclimate Applications [J]. Signal Processing, 2013, 93(5):1079-1094.
[5]WU H T , CHAN Y H , LIN Y T, et al. Using Synchrosqueezing Transform to Discover Breathing Dynamics from ECG Signals [J]. Appl. Comput. Harmon. Anal., 2014, 36(2):354-359.
[6]HERRERA R H, HAN Jiajun, van der BAAN M. Applications of the Synchrosqueezing Transform in Seismic Time-frequency Analysis [J]. Geophysics, 2014, 79(3):V55-V64.
[7]厉祥.基于SST和神经网络的风电功率预测[D].武汉:武汉科技大学,2014.
LI Xiang. Wind Power Prediction Based on SST and Neural Network [D]. Wuhan: Wuhan University of Science and Technology, 2014.
[8]褚福磊,彭志科,冯志鹏,等.机械故障诊断中的现代信号处理方法[M].北京:北京出版社,2009.
CHU Fulei, PENG Zhike, FENG Zhipeng, et al. Modern Fault Processing in Mechanical Fault Diagnosis Method [M]. Beijing: Beijing Press, 2009.