Processing method of EMD endpoint effect based on SVRM extension

Aiming at the problem of endpoint effect in empirical mode decomposition (EMD), the application method of support vector regression machine (SVRM) in EMD extension data prediction is studied. Firstly, the basic principle, data extension method and parameter setting of SVRM are introduced. Secondly, several application methods of SVRM in EMD extension are studied to analyze and verify the operational efficiency and decomposition accuracy characteristics of each method respectively. Finally, the proposed extension method based on SVRM extreme value point prediction can greatly improve the operation efficiency of SVRM long time extension. The simulation signal analysis shows that the SVRM extreme point prediction extension method not only improves the accuracy and reliability of EMD decomposition, but also effectively inhibits the end-point effect phenomenon, significantly reduces the SVRM extension time, and improves the practicability of EMD method.