Improved EEMD in the Application of Signal Singularity Detection
| Periodical | Advanced Materials Research (Volumes 518 - 523) |
|---|---|
| Main Theme | Advances in Environmental Science and Engineering |
| Edited by | Reza Iranpour, Ji Zhao, Aijie Wang, Fenglin Yang and Xinyong Li |
| Pages | 3847-3851 |
| DOI | 10.4028/www.scientific.net/AMR.518-523.3847 |
| Citation | Mei Jun Zhang et al., 2012, Advanced Materials Research, 518-523, 3847 |
| Online since | May, 2012 |
| Authors | Mei Jun Zhang, Chuang Wang, Hao Chen, Qun Zhang Tu |
| Keywords | EEMD, Endpoint Effect, IMF, Signal Processing |
| Price | US$ 28,- |
In order to solve the endpoint effect and modal aliasing phenomenon in EMD and EEMD,Improved EEMD is put forward, and the application in signal singularity detection is researched in this paper. The improved EEMD will signal drops down into a series of different IMF to highlight the different local characteristics of original data, and then calculate Hilbert marginal spectrum and time-frequency spectrum to determine the frequency of these mutations and mutations position. To compared with FT, STFT, WVD,WT, EMD and EEMD etc, No cross-terms and no false IMF components are produced in the Hilbert time-frequency spectrum of the improved EEMD. Different frequency components and frequency mutations position are clearly distinguished at the same time. The Hilbert time-frequency spectrum of the improved EEMD has more superior detection signal singularity ability.