Signal processing methods are essential in scientific research, and time-frequency analysis
techniques such as Fourier Transform constitute an important progress in data analysis, but …

This work reviews the advancements in the non-conventional analysis of speech signals,
particularly from an AM-FM analysis point of view. The benefits of such an analysis, as …

A modified version of empirical mode decomposition (EMD) is presented to solve the mode
mixing problem. The sifting process is completed using a time varying filter technique. In this …

A time varying filtering based empirical mode decomposition (EMD)(TVF-EMD) method was
proposed recently to solve the mode mixing problem of EMD method. Compared with the …

The reliable and accurate prediction of groundwater levels is important to improve water-use
efficiency in the development and management of water resources. Three nonlinear time …

This work deals with the decomposition of a signal into a collection of intrinsic mode
functions. More specifically, we aim to revisit Empirical Mode Decomposition (EMD) based …

Of the characteristics of tight sandstone reservoirs, heterogeneity is one of the most difficult
characteristics to analyze. Heterogeneity is mainly manifested in three properties: lithology …

It is a difficult process to detect abnormal heart beats, known as arrhythmia, in long-term
ECG recording. Thus, computer-aided diagnosis systems have become a supportive tool for …

Local mean decomposition (LMD) is widely used in signal processing and fault diagnosis of
rotating machinery as an adaptive signal processing method. It is developed from the …

Empirical mode decomposition (EMD) lacks a strong theoretical support although
extensively applied. We propose a theoretical framework for a succinct EMD in this work …