A Statistical Approach to Signal Denoising Using VMD and CVM

Data for: A Statistical Approach to Signal Denoising Based on Data-driven Multiscale Representation

Description of this data
This MATLAB code implements a data-driven signal denoising method published in Digital Signal Processing Journal and can be accessed from https://www.sciencedirect.com/science/article/pii/S1051200420302414?via%3Dihub.

Cite this article when using this code: Khuram Naveed, Muhammad Tahir Akhtar, Muhammad Faisal Siddiqui, Naveed ur Rehman, "A statistical approach to signal denoising based on data-driven multiscale representation", Digital Signal Processing, Vol. 108, pp. 102896, 2021.

Following are the details of the code

VMD_CVM_Main: This is the main file from where the whole code can be executed to perform denoising
Prop_VMD_CVM: Implements the the proposed denoising algorithm.
VMD.m: Performs variational mode decomposition of the noisy signal.
cvm.m: Implements the Cramer Von Mises statistic of the selected segment of the data
threshvspfa: Estimates threshold for a given Pfa using the rejected noise modes.
cdf_calc.m: matlab code to compute EDF
mse.m: Compute mean squared error for the denoised signal
snr.m: Compute signal to noise ratio for the denoised signal
sofar.mat, taichi.mat and ECGsig.mat contain the real world signals, of the same name, used in this study.

This code is also freely available at Elseveir Mendleys and can be accessed from the link: https://data.mendeley.com/datasets/g2wv44fsb3/draft?a=6a07a1d3-a4e0-4b05-80e6-0eedbbcd4080