Adaptive mode decomposition based on the instantaneous frequency basis space

Abstract

Signal decomposition has attracted increasing interest in various applications in recent years. This paper proposes a new mode decomposition algorithm, called “mode decomposition based on the instantaneous frequency basis space” (IFBMD), to decompose complex chirp signals superposed with multiple-mode signals with a low-frequency instantaneous frequency (IF). In IFBMD, a global optimization algorithm is combined with an alternating iterative computation method to extract the optimal IF of the modes from the low-frequency IF basis space. In addition, to avoid the limitation of a fixed number of modes, an adaptive IFBMD is designed based on a scale-factor iteration approach that can extract modes successively. This new scaling-factor updating method can be widely usable to improve other mode-decomposition algorithms. Compared with other well-known algorithms, IFBMD has been proved to be superior in performance.