An Efficient ECG Denoising Technique Based on Non-local Means Estimation and Modified Empirical Mode Decomposition

Real‐time speech enhancement using optimised empirical mode decomposition and non‐local means estimation

“…The maximum‐frequency IMFs are processed using the technique of smooth thresholding. The threshold parameter can be calculated by using the below expression [24] From the above expression represents the content of maximal frequency signal and represents the stable signal. If the signal of the original must sustain.…”

“…Singh et al [24] presented one method that was electrocardiogram (ECG) de‐noising in terms of the useful integration NLM estimation as well as EMD. To address the problem of under average region in patch‐based method, the de‐noised signal received through NLM was decomposed as IMFs utilising EMD.…”

An Efficient Porcine Acoustic Signal Denoising Technique Based on EEMD‐ICA‐WTD

“…e noise mainly concentrates in high frequency. erefore, the rst few IMFs contain both the information of porcine acoustic signal and noise [15]. PE of each IMF is calculated.…”

“…erefore, Fast-ICA is used to extract the ICs of noise-dominant IMFs to concentrate the noise and real information and improve SNR of components. (3) As the rst IMF contains much of the high-frequency noise [15], the correlation coe cients of ICs and the rst IMF are calculated. If the correlation coe cient is more than 0.8, the IC will be regarded as noise and will be removed.…”

“…e independent components (IC) of noise-dominant IMFs are extracted by independent component analysis (ICA). As the first IMF contains much of the high-frequency noise [15], the correlation coefficients of ICs and the first IMF are calculated to recognize noise ICs. After that, the noise ICs are removed and the other ICs are denoised by WTD.…”