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.
