Research on Nonstationary Signal Denoising Based on EEMD Filter

To reduce the noise in the signal in nonstationary signals, a new technique based on EEMD(Ensemble Empirical Mode Decomposition) was studied for decomposing signal. With the EEMD the extremums of the signal was used as scales to decompose data in the time domain and get the IMFs (Intrinsic Mode Function) with their frequencies from high to low. Then based the frequency spectrum from FT(Fourier Transform) of each IMF a new filter can be establish to denosing signals. Furthermore the nonstationary signals with different SNR (Signal to Noise Ratio) were simulated to validate this filter and compared denosing method based on wavelet analysis. The comparing indexes showed that the denosing effect with EEMD filter excelled the wavelet method appreciably, but avoid the difficulty to select a proper wavelet. With this method, the signal was decomposed based on the scales in itself and have the most adaptivity.