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Noise reduction method of ship radiated noise with ensemble empirical mode decomposition of adaptive noise

Authors: Yang Hong; Li Ya-an; Li Guo-Hui;

Noise reduction method of ship radiated noise with ensemble empirical mode decomposition of adaptive noise

Abstract

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.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Top 10%
Average
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