Name
Abstract | ||
|---|---|---|
Empirical Mode Decomposition (EMD) is an effective, non-linear and non-stationary data analysis method, which can decompose the original signal into several intrinsic mode functions(IMFs). However the frequency resolution of EMD has not been thoroughly investigated so far. In this paper a signal which contains two different frequency components was do composed with EMD, and subsequently the obtained IMFs was compared to evaluate the frequency resolution of EMD. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CIS.2010.151 | CIS |
Keywords | Field | DocType |
different frequency component,original signal,frequency resolution,signal frequency domain resolution,intrinsic mode function,non-stationary data analysis method,empirical mode decomposition,frequency domain,data analysis,data analysis methods,interpolation,fitting,automation,resolution,spline,frequency domain analysis,time frequency analysis | Frequency domain,Spline (mathematics),Frequency resolution,Pattern recognition,Computer science,Interpolation,Signal frequency,Speech recognition,Artificial intelligence,Time–frequency analysis,Machine learning,Hilbert–Huang transform | Conference |
Citations | PageRank | References |
1 | 0.40 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meng Hou | 1 | 1 | 0.40 |
| Zeng-Li Liu | 2 | 8 | 1.88 |
| Haiyan Quan | 3 | 15 | 2.15 |
| Yongde Zhang | 4 | 37 | 10.13 |