In signal processing field, mode decomposition is one of the most important branches. Many
existing decomposition methods are mainly used to deal with narrow-band signals. If the …

Group-sparse mode decomposition (GSMD) is an efficient signal decomposition algorithm
for separating harmonic signals, but fails to split modes for periodic pulse signals. In order to …

A new signal decomposition algorithm is developed in this paper. The goal of signal
decomposition is to decompose a complex and nonstationary signal into a set of basic …

Due to the problem of modal confusion and extreme sensitivity to strong noise in signal
decomposition using group-sparse mode decomposition, this paper proposes a new signal …

Group-sparse mode decomposition (GSMD) is a novel signal decomposition algorithm
based on the concept of group sparse. It is fast, robust against noise, and has good anti …

In signal decomposition, a complex and nonstationary signal is decomposed into a set of
basic functions, usually called intrinsic mode functions (IMFs). In multivariate signal …

Although traditional signal processing methods have good decomposition performance in
multimodal signals, they lack theoretical research on periodic pulse signals, resulting in …

As a new signal decomposition method, sparse random mode decomposition (SRMD) does
not depend on the signal sampling process and has good anti-mode aliasing performance …

Group-sparse mode decomposition (GSMD) is a decomposition method designed based on
the group sparse property of signals in frequency domain. It is proved to be highly efficient …

A new modal decomposition algorithm using Particle Swarm Optimization for optimal
vibration signal spectrum modal decomposition in this paper. The modal parameters of …