
doi: 10.3397/1/376374
Ensemble empirical mode decomposition method (EEMD) is important improvement of the empirical mode decomposition (EMD), but it still leaves some annoying difficulties unresolved, such as large computational cost and reconstruction error. To solve above problems of the EEMD, a new method named EEMD of adaptive noise (EEMDAN) is proposed, which can obtain accurate time-frequency distribution of the original signal. In addition, aiming at the non-linear, non-stationary and non-Gaussian characteristics of underwater acoustic signal, a noise reduction method based on the EEMDAN is also proposed. Each order intrinsic mode function (IMF) can be obtained by the EEMDAN for noisy Lorenz signal and three different types of real ship radiated noises. The components of the signal and noise can be adaptively determined by IMF correlation coefficient based on energy density and average cycle. The results show that the method is effective and a very clean signal can be obtained.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
