An improved time-frequency representation based on nonlinear mode decomposition and adaptive optimal kernel
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Date
Authors
Xin, Zhang
Jie, Shao
Wenwei, An
Tiantian, Yang
Malekian, Reza
Journal Title
Journal ISSN
Volume Title
Publisher
Kaunas University of Technology
Abstract
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.
Description
Keywords
Time-frequency representation (TFR), Adaptive optimal kernel (AOK), Nonlinear mode decomposition (NMD)
Sustainable Development Goals
Citation
Xin, Z, Jie, S, Wenwei, A, Tiantian, Y & Malekian, R 2016, 'An improved time-frequency representation based on nonlinear mode decomposition and adaptive optimal kernel', Elektronika ir Elektrotechnika, vol. 22, no. 4, pp. 52-57.