The method of extreme point extension based on clustering least squares and slope was proposed to address the endpoint effect that could occur in signal denoising by empirical mode decomposition (EMD). This method fully considered the influence of noise on the continuation method, described the changing trend of global extreme points using the clustering least square method, and determined the coordinate information of the continuation points by combining the local characteristics of the signal boundary. The performance of the algorithm was evaluated by similarity coefficient, root mean square error and orthogonality level through the study of simulation signal and gyro example signal. The experimental results show that the method proposed in this paper can effectively suppress the endpoint effect of EMD and avoid the pollution of the endpoint effect to the intermediate data to the greatest extent, thus improving the accuracy and reliability of signal denoising, and providing a feasible and effective solution for the application of EMD in signal processing.
文可,张爱军. 基于聚类最小二乘法和斜率相结合的极值点延拓方法[J]. 科学技术与工程, 2024, 24(21): 8980-8986. Wen Ke, Zhang Aijun. Extreme point continuation method based on clustering least square method and slope[J]. Science Technology and Engineering,2024,24(21):8980-8986.