[1]Li Peng, Kong Fanrang, He Qinbo, et al. Multiscale Slope Feature Extraction for Rotating Machinery Fault Diagnosis Using Wavelet Analysis[J]. Measurement, 2013, 46(1):497-505.
[2]秦亮,石林锁,张亚洲.基于盲信号提取的机械振动信号消噪方法研究[J]. 电子测量技术,2009,32(6):4-6.
Qin Liang, ShiLinsuo, Zhang Yazhou. Research of the Noise Method for Mechanical Vibration Signal Based on Blind Signal Extraction[J]. Electronic Measurement Technology,2009,32(6):4-6.
[3]Zhang Hongjuan, Wang Guinan, Cai Pingmei, et al. A Fast Blind Source Separation Algorithm Based on the Temporal Structure of Signals[J]. Neurocomputing, 2014, 139(2):261-271.
[4]Li Y Q, Cichocki A, Amari S. Analysis of Sparse Presentation and Blind Source Separation[J]. Neural Computation, 2004, 16(6):1193-1234.
[5]Gu Fanglin, Zhang Hang, Zhu Desheng. Blind Separation of Non-stationary Sources Using Continuous Density Hidden Markov Models[J]. Digital Signal Processing, 2013, 23(5):1549-1564.
[6]Luengo D, Santanmari L. A Fast Blind SIMO Channel Identification Algorithm for Sparse Sources[J]. IEEE Signal Precessing Letters, 2003, 10(5): 184-151.
[7]Takehiro H, Kazushi N, Akihiro I. Wacelet-based Underdetermined Blind Source Separation of Speech Mixtures[C]//International Conference on Control, Automation and Systems. Seoul, Korea, 2007: 2790-2794.
[8]Blgdan M. Source Separation From Single-channel Recordings by Combining Emperical-mode Decomposition and Independent Component Analysis [J]. IEEE Transaction on Biomedical Engineering,2010, 57(9): 2188-2196.
[9]李晓晖,傅攀. 基于EEMD的单通道盲源分离在轴承故障诊断中的应用[J]. 中国机械工程,2014,25(7):924-930.
Li Xiaohui, Fu Pan. Application of Signal-channel Blind Source Separation Based on EEMD in Bearing Fault Diagnosis[J]. China Mechanical Engineering, 2014, 25(7):924-930.
[10]Donoho D L. Compressed Sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4):1289-1306.
[11]Hou T Y, Shi Zuoqiang. Adaptive Data Analysis Via Sparse Time-frequency Representation[J]. Advances in Adaptive Data Analysis, 2011, 3(1/2):1-28. |