Data driven time-frequency analysis based on empirical mode decomposition and adaptive optimal kernel

Lu, Rongjun; Zhou, Bin; Gao, Wei

doi:10.1109/icacte.2010.5579680

Cited by 1 publication

(2 citation statements)

References 8 publications

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“…With the advantages compared to EMD, EEMD is chosen to replace EMD to be integrated with AOK to compute the time-frequency representation [9]. While EEMD + AOK method performs a little better than EMD+AOK on removing the noise and mode mixing, it still cannot be regarded as a real noise robust method compared with many approaches and its performance do not meet our expectations.…”

Section: B Eemd + Aokmentioning

confidence: 99%

“…However, AOK normally performs well only for single component signals [8]. To reduce the interference of the cross terms in AOK when processing multi-component signals, a TFR method integrating EMD with AOK (EMD + AOK) can suppress the cross terms to a certain extent, but being quite sensitive to noise [9]. Since EEMD is more effective in resisting noise than EMD, EEMD + AOK can be used to improve the noise robustness to some degree but not enough [5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Improved Time-Frequency Representation based on Nonlinear Mode Decomposition and Adaptive Optimal Kernel

Xin¹,

Shao²,

Wenwei³

et al. 2016

ElAEE

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Time-frequency representation (TFR) based on Adaptive Optimal Kernel (AOK) normally performs well only for monocomponent signals and has poor noise robustness. To overcome the shortcomings of AOK TFR mentioned above, a new TFR algorithm is proposed here by integrating nonlinear mode decomposition (NMD) with AOK TFR. NMD is used to decompose multicomponent signals into a bundle of meaningful oscillations and then AOK is applied to compute the TFR of individual oscillations, finally all these TFRs are summed together to generate one TFR. Through quantitative comparison with other TFR methods to both simulated and real signals, the superiority of proposed TFR based on NMD and AOK on removing noise and many other measurement index of TFR are shown.

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Section: B Eemd + Aokmentioning

confidence: 99%