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 …

In order to overcome the influence of non-adaptive selection of non-stationary coefficient
threshold of compound interpolation envelope (CIE) method on decomposition performance …

The real-time analysis of time-varying data has become extremely significant in mechanical
systems. The Hilbert–Huang transform (HHT) is a recent development in signal processing …

The construction of Bézier curves and surfaces with shape parameters is one of the most
popular areas of research in CAD. In this paper, we present a novel shape-adjustable …

The feature extraction of marine vessel-radiated noise (MVRN) under the complex ocean
background is explored. To this end, a hybrid approach is presented based on the analysis …

As a powerful time-frequency signal analysis technique, empirical mode decomposition
(EMD) has been commonly applied in fault diagnosis. However, the cubic spline-curve often …

In this paper, a novel diagnosis method based on adaptive scale decomposition and
weighted multikernel correntropy (ASD-WMKC) is developed to diagnose the faults of …

The construction of the generalized Bézier model with shape parameters is one of the
research hotspots in geometric modeling and CAGD. In this paper, a novel shape-adjustable …

The empirical mode decomposition (EMD) is a method that is commonly applied to extract
the intrinsic mode functions (IMFs) of a signal by a sifting process, which requires imposing …

Trajectory planning is an important issue for manipulators and robots. To get a optimal
trajectory, many constraints including actuators specifications, motion range of joints …