Name
Abstract | ||
|---|---|---|
In this paper, a signal-filtering method based on empirical mode decomposition is proposed. The filtering method is a fully data-driven approach. A noisy signal is adaptively decomposed into intrinsic oscillatory components called intrinsic mode functions (IMFs) by means of an algorithm referred to as a sifting process. The basic principle of the method is to make use of partial reconstructions of... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TIM.2007.907967 | IEEE Transactions on Instrumentation and Measurement |
Keywords | Field | DocType |
Filtering,Nonlinear filters,Additive white noise,Gaussian noise,Signal processing,Wiener filter,AWGN,Wavelet packets,Signal processing algorithms,Low-frequency noise | Signal processing,Filter (signal processing),Electronic engineering,Filtering theory,Additive white Gaussian noise,Signal reconstruction,Signal transfer function,Mathematics,Energy distribution,Hilbert–Huang transform | Journal |
Volume | Issue | ISSN |
56 | 6 | 0018-9456 |
Citations | PageRank | References |
24 | 1.66 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A Boudraa | 1 | 215 | 22.86 |
| Jean-Christophe Cexus | 2 | 75 | 9.06 |