Abstract
Classic coherence analysis has been commonly used as a effective method for the analysis of stationary signals. To study the instantaneous coherence between non-stationary signals, we extended the concept of coherence to time-varying coherence using some time-frequency analysis methods. Wavelet-based coherence is one of the most widely used time-varying coherence methods, but few researchers have applied Hilbert-Huang transform (HHT) to coherence analysis, which also has excellent characteristics of time-frequency analysis. Therefore, this paper proposed the concept of HHT coherence, derived its method based on wavelet coherence and verified its feasibility. Then, we compared wavelet coherence and HHT coherence from three different aspects: the time-frequency resolution, effects of noise and adaptivity. The results of different simulating signals demonstrated that HHT coherence had higher time resolution, frequency resolution and more adaptivity than wavelet coherence under ideal conditions. However, due to its imperfect algorithm, the time-frequency resolution of HHT coherence was reduced by the effect of mode mixing, boundary distortion and noise. By contrast, wavelet coherence is more stable.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.