WAVELET THRESHOLD TRANSFORM AND EMPIRICAL MODE DECOMPOSITION JOINT DENOISING OF SIGNAL
Journal: Applied Computer Letters (ACL)
Author: Bingkun Gao, Xingyue Cui, Li Zhang, Lingchuan Sun
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Wavelet transforms and empirical mode decomposition are powerful tools for processing non-stationary and nonlinear signals, suitable for de-noising nuclear magnetic resonance logging echo signal. This paper introduces that signal reflect well exponential decay characteristics of echo signal after utilizing the wavelet transform to threshold processing the nuclear magnetic resonance logging echo signal, and reflect commendable adaptability after using the empirical mode decomposition dealing with the echo signal in logging. By taking advantage of processing logging echo signal through wavelet transform and empirical mode decomposition, not only can obtain higher signal-to-noise ratio compared with single method, but also get smoother signal.