Abstract
Nearly bandlimited signals play an important role in the biomedical signal processing community. The common method to analyze these signals is via the empirical mode decomposition approach which decomposes the non-stationary signals into the sums of the intrinsic mode functions. However, this method is computational demanding. A natural idea to reduce the computational cost is via the block processing. However, the severe boundary effect would happen due to the discontinuities between two consecutive blocks. In order to solve this problem, this paper proposes to realize the parallel implementation via polyphase representation. That is, the empirical mode decomposition is implemented on each polyphase component of the original signal. Then each sub-signals are combined after upsampling. The simulation results show that our proposed method achieves the approximate intrinsic mode functions both qualitatively and quantitatively very close to the true intrinsic mode functions. Besides, compared with the conventional block processing method which significantly suffered from the boundary effect problem, our proposed method does not have this issue.
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Acknowledgements
This paper was supported partly by the National Nature Science Foundation of China (Nos. U1701266, 61372173 and 61671163), the Team Project of the Education Ministry of the Guangdong Province (2017KCXTD011), the Guangdong Higher Education Engineering Technology Research Center for Big Data on Manufacturing Knowledge Patent (No. 501130144) and Hong Kong Innovation and Technology Commission, Enterprise Support Scheme (No. S/E/070/17).
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Ye, Q., Ling, B.WK., Lun, D.P.K. et al. Parallel implementation of empirical mode decomposition for nearly bandlimited signals via polyphase representation. SIViP 14, 225–232 (2020). https://doi.org/10.1007/s11760-019-01546-w
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DOI: https://doi.org/10.1007/s11760-019-01546-w