Adaptive generalized dispersive mode decomposition (AGDMD)

A data-driven approach for nonlinear dispersive component extraction

The matlab codes permit to reproduce some results in the paper: Wang H, Chen S, Zhai W, Adaptive generalized dispersive mode decomposition: A data-driven approach for nonlinear dispersive component extraction in mechanical systems, Journal of Sound and Vibration, 2025. The algorithm used in the paper is an improved version of that in the paper:Wang H, Chen S, Zhai W, Data-driven adaptive chirp mode decomposition with application to machine fault diagnosis under non-stationary conditions, Mechanical Systems and Signal Processing, 2023; and the paper: Chen S, Wang K, Peng Z, et al, Generalized dispersive mode decomposition: Algorithm and applications, Journal of Sound and Vibration, 2021. Some of the scripts are adopted from the papers: Chen S, Yang Y, Peng Z, et al, Adaptive chirp mode pursuit: Algorithm and applications, Mechanical Systems and Signal Processing, 2018. Chen S, Dong X, Peng Z, et al, Nonlinear Chirp Mode Decomposition: A Variational Method, IEEE Transactions on Signal Processing, 2017. Wang H, Chen S, Zhai W, Variational generalized nonlinear mode decomposition: Algorithm and applications, Mechanical Systems and Signal Processing, 2023.

Copyright (c) belongs to the authors of the papers. An acknowledgment for the codes and the citations about the papers above should be included in the publications as long as the codes are used.