Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …

Data analysis has been one of the core activities in scientific research, but limited by the
availability of analysis methods in the past, data analysis was often relegated to data …

During the late 1990s, Huang introduced the algorithm called Empirical Mode
Decomposition, which is widely used today to recursively decompose a signal into different …

Traffic flow prediction with high accuracy is definitely considered as one of most important
parts in the Intelligent Transportation Systems. As interfering by some external factors, the …

This article addresses data-driven time-frequency (TF) analysis of multivariate signals, which
is achieved through the empirical mode decomposition (EMD) algorithm and its noise …

Vibrations of complex structures such as bridges mostly present nonlinear and non-
stationary behaviors. Recently, one of the most common techniques to analyze the nonlinear …

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 …

The remote sensing community has identified data fusion as one of the key challenging
topics of the 21st century. The subject of image fusion in two-dimensional (2D) space has …

Unlike the healthy cells in the breast tissue, cancerous breast cells are unwelcome and have
strange properties. In both sexes, this will quickly expand and infiltrate adjacent tissue …

A multi-dimensional ensemble empirical mode decomposition (MEEMD) for multi-
dimensional data (such as images or solid with variable density) is proposed here. The …