Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble Approaches
The empirical mode decomposition (EMD) is an established method for the time-frequency analysis of nonlinear and nonstationary signals. However, one major drawback of the EMD is the mode mixing effect. Many modifications have been made to resolve the mode mixing effect. In particular, disturbance-as...
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| Format: | Article |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8386746/ |
| _version_ | 1818331698456166400 |
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| author | Yung-Hung Wang Kun Hu Men-Tzung Lo |
| author_facet | Yung-Hung Wang Kun Hu Men-Tzung Lo |
| author_sort | Yung-Hung Wang |
| collection | DOAJ |
| description | The empirical mode decomposition (EMD) is an established method for the time-frequency analysis of nonlinear and nonstationary signals. However, one major drawback of the EMD is the mode mixing effect. Many modifications have been made to resolve the mode mixing effect. In particular, disturbance-assisted EMDs, such as the noise-assisted EMD and the masking EMD, have been proposed to resolve this problem. These disturbance-assisted approaches have led to a better performance of the EMD in the analysis of real-world data sets, but they may also have two side effects: the mode splitting and residual noise effects. To minimize or eliminate the mode mixing effect while avoiding the two side effects of traditional disturbance-assisted EMDs, we propose an EMD-based algorithm assisted by sinusoidal functions with a designed uniform phase distribution with a comprehensive theoretical explanation for the substantial reduction of the mode splitting and the residual noise effects simultaneously. We examine the performance of the new method and compare it to those of other disturbance-assisted EMDs using synthetic signals. Finally numerical experiments with real-world examples are conducted to verify the performance of the proposed method. |
| first_indexed | 2024-12-13T13:23:59Z |
| format | Article |
| id | doaj.art-53f7cbc1cc1348c7b41e974811a73850 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T13:23:59Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-53f7cbc1cc1348c7b41e974811a738502022-12-21T23:44:20ZengIEEEIEEE Access2169-35362018-01-016348193483310.1109/ACCESS.2018.28476348386746Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble ApproachesYung-Hung Wang0Kun Hu1Men-Tzung Lo2https://orcid.org/0000-0003-2630-4945Research Center for Adaptive Data Analysis, National Central University, Taoyuan, TaiwanMedical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USAGraduate Institute of Translational and Interdisciplinary Medicine, National Central University, Taoyuan, TaiwanThe empirical mode decomposition (EMD) is an established method for the time-frequency analysis of nonlinear and nonstationary signals. However, one major drawback of the EMD is the mode mixing effect. Many modifications have been made to resolve the mode mixing effect. In particular, disturbance-assisted EMDs, such as the noise-assisted EMD and the masking EMD, have been proposed to resolve this problem. These disturbance-assisted approaches have led to a better performance of the EMD in the analysis of real-world data sets, but they may also have two side effects: the mode splitting and residual noise effects. To minimize or eliminate the mode mixing effect while avoiding the two side effects of traditional disturbance-assisted EMDs, we propose an EMD-based algorithm assisted by sinusoidal functions with a designed uniform phase distribution with a comprehensive theoretical explanation for the substantial reduction of the mode splitting and the residual noise effects simultaneously. We examine the performance of the new method and compare it to those of other disturbance-assisted EMDs using synthetic signals. Finally numerical experiments with real-world examples are conducted to verify the performance of the proposed method.https://ieeexplore.ieee.org/document/8386746/UPEMDEMDuniform phasemode splittingresidual noise |
| spellingShingle | Yung-Hung Wang Kun Hu Men-Tzung Lo Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble Approaches IEEE Access UPEMD EMD uniform phase mode splitting residual noise |
| title | Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble Approaches |
| title_full | Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble Approaches |
| title_fullStr | Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble Approaches |
| title_full_unstemmed | Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble Approaches |
| title_short | Uniform Phase Empirical Mode Decomposition: An Optimal Hybridization of Masking Signal and Ensemble Approaches |
| title_sort | uniform phase empirical mode decomposition an optimal hybridization of masking signal and ensemble approaches |
| topic | UPEMD EMD uniform phase mode splitting residual noise |
| url | https://ieeexplore.ieee.org/document/8386746/ |
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