Fourier-Bessel representation for signal processing: A review
Several applications, analysis and visualization of signal demand representation of time-
domain signal in different domains like frequency-domain representation based on Fourier …
domain signal in different domains like frequency-domain representation based on Fourier …
A comparative study of four kinds of adaptive decomposition algorithms and their applications
T Liu, Z Luo, J Huang, S Yan - Sensors, 2018 - mdpi.com
The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can
decompose signals into several narrow-band components, which is advantageous to …
decompose signals into several narrow-band components, which is advantageous to …
A novel fusion based convolutional neural network approach for classification of COVID-19 from chest X-ray images
Coronavirus disease is a viral infection caused by a novel coronavirus (CoV) which was first
identified in the city of Wuhan, China somewhere in the early December 2019. It affects the …
identified in the city of Wuhan, China somewhere in the early December 2019. It affects the …
Extraction of weak fault transients using variational mode decomposition for fault diagnosis of gearbox under varying speed
Non-stationary vibration signals of a gearbox under varying speed display complicated
modulations, which lead to intense sidebands thereby resulting in difficulty to identify the …
modulations, which lead to intense sidebands thereby resulting in difficulty to identify the …
FBDM based time-frequency representation for sleep stages classification using EEG signals
V Gupta, RB Pachori - Biomedical Signal Processing and Control, 2021 - Elsevier
In this paper, we have proposed a new method of time-frequency representation (TFR)
which is based on the Fourier-Bessel decomposition method (FBDM). This proposed …
which is based on the Fourier-Bessel decomposition method (FBDM). This proposed …
Epilepsy seizure detection using kurtosis based VMD's parameters selection and bandwidth features
M Chakraborty, D Mitra - Biomedical Signal Processing and Control, 2021 - Elsevier
This paper presents an automated seizure detection method based on variational mode
decomposition (VMD). In VMD, the number of decomposed modes K and the penalty …
decomposition (VMD). In VMD, the number of decomposed modes K and the penalty …
Automated detection of severity of hypertension ECG signals using an optimal bi-orthogonal wavelet filter bank
Hypertension (HPT) is a serious risk factor for cardiovascular disease and if not controlled in
the early stage, can lead to serious complications. Long-standing HPT can induce heart …
the early stage, can lead to serious complications. Long-standing HPT can induce heart …
Early fault diagnosis for planetary gearbox based on adaptive parameter optimized VMD and singular kurtosis difference spectrum
C Wang, H Li, G Huang, J Ou - IEEE Access, 2019 - ieeexplore.ieee.org
Variational mode decomposition (VMD) is widely used in the condition monitoring and fault
diagnosis of rotary machinery for its unique advantages. An adaptive parameter optimized …
diagnosis of rotary machinery for its unique advantages. An adaptive parameter optimized …
Automated characterization of cyclic alternating pattern using wavelet-based features and ensemble learning techniques with eeg signals
Sleep is highly essential for maintaining metabolism of the body and mental balance for
increased productivity and concentration. Often, sleep is analyzed using macrostructure …
increased productivity and concentration. Often, sleep is analyzed using macrostructure …
Research on a novel improved adaptive variational mode decomposition method in rotor fault diagnosis
X Yan, Y Liu, W Zhang, M Jia, X Wang - Applied Sciences, 2020 - mdpi.com
Variational mode decomposition (VMD) with a non-recursive and narrow-band filtering
nature is a promising time-frequency analysis tool, which can deal effectively with a non …
nature is a promising time-frequency analysis tool, which can deal effectively with a non …