A signal de-noising algorithm based on correlation techniques
Xingye Li, Linlin Ma, Yi Ma · 2007
A new periodic signal de-noising method is proposed based on correlation techniques. This new method can be regarded as selecting the frequency components which mainly attributable to the original periodic signal from the noisy signal by using the correlation techniques and DFT (discrete Fourier transform). Experimental results indicate that our proposed method is not only effective when the noise is white noise, but also can extract a periodic signal from the colored noise. It is also shown in the experiment that our method is better than wavelet thresholding de-noising methods.