基于参数优化变分模态分解的信号降噪方法OA北大核心

In allusion to the problem of difficult removal of electromyographic interference noise in electrocardiogram(ECG)signals,a method of signal denoising based on parameter-optimized variational mode decomposition(VMD)is proposed.The beluga whale optimization(BWO)algorithm is improved by designing the dynamic boundary strategy and inverse population generation.The improved BWO algorithm is used for the adaptive optimization of the VMD parameters to determine the number of decomposition layers K and the penalty factor α.The noise-containing ECG signal is decomposed to obtain k intrinsic mode function(IMF)components,and the correlation coefficient method is used to identify the effective modes and noise-containing modes.The noise-dominated modal components are noise-reduced by means of the wavelet thresholding,and the dominant modes and noise-reduced modes of the reconstructed signal are reconstructed.The simulation signals and ECG signals with real EMG interference are processed for the denoising.The experimental results show that the proposed method is superior to wavelet threshold denoising method,EMD method and EMD-wavelet threshold denoising method,and the autocorrelation coefficient of real ECG signals with noise can reach more than 0.91 after denoising.