Dynamic Bayesian wavelet transform: New methodology for extraction of repetitive transients

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• 作者：Dong Wang ; ^{dongwang4-c@my.cityu.edu.hk} ; Kwok-Leung Tsui ^{kltsui@cityu.edu.hk}
• 关键词：Bayesian inference ; Wavelet parameter distribution ; Dynamic Bayesian wavelet transform ; Repetitive transients
• 刊名：Mechanical Systems and Signal Processing
• 出版年：2017
• 出版时间：1 May 2017
• 年：2017
• 卷：88
• 期：Complete
• 页码：137-144
• 全文大小：1529 K
• 卷排序：88

文摘

Dynamic Bayesian wavelet transform as new methodology is proposed. Repetitive transients are extracted by using Dynamic Bayesian wavelet transform. The proposed method can be initialized by many fast detection algorithms. The proposed method is convergent as iterations increase. The proposed method can be extended to find the optimal parameters of other signal processing methods.