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Successive variational mode decomposition
Variational mode decomposition (VMD) is a powerful technique for concurrently
decomposing a signal into its constituent intrinsic modes. However, the performance of VMD …
decomposing a signal into its constituent intrinsic modes. However, the performance of VMD …
[HTML][HTML] Field programmable gate array applications—A scientometric review
Field Programmable Gate Array (FPGA) is a general purpose programmable logic device
that can be configured by a customer after manufacturing to perform from a simple logic gate …
that can be configured by a customer after manufacturing to perform from a simple logic gate …
Recursive sliding DFT algorithms: A review
This paper reviews different recursive structures of Sliding Discrete Fourier Transform
(SDFT) algorithms. Normally, a SDFT algorithm is introduced to design a filter or to compute …
(SDFT) algorithms. Normally, a SDFT algorithm is introduced to design a filter or to compute …
An efficient removal of power-line interference and baseline wander from ECG signals by employing Fourier decomposition technique
Baseline wander (BW) and power-line interference (PLI) tend to occur in every recorded
electrocardiogram (ECG) signal and can significantly deteriorate the quality of the signal …
electrocardiogram (ECG) signal and can significantly deteriorate the quality of the signal …
Variational mode extraction: A new efficient method to derive respiratory signals from ECG
ECG-derived respiratory (EDR) signal is an effective and inexpensive method to monitor the
respiration. Previous studies have shown that the empirical mode decomposition (EMD) …
respiration. Previous studies have shown that the empirical mode decomposition (EMD) …
A deep learning-based framework For ECG signal denoising based on stacked cardiac cycle tensor
The Electrocardiogram (ECG) signal is one of the frequently used non-invasive
physiological measurement techniques for heart diagnosis. However, ECG signal is often …
physiological measurement techniques for heart diagnosis. However, ECG signal is often …
An end-to-end 12-leading electrocardiogram diagnosis system based on deformable convolutional neural network with good antinoise ability
Electrocardiogram (ECG) is a tool to help judge heart activity. In recent years, the
convolutional neural network (CNN) and various deep learning algorithms have been widely …
convolutional neural network (CNN) and various deep learning algorithms have been widely …
A robust ECG signal enhancement technique through optimally designed adaptive filters
Electrocardiogram (ECG) signals are widely used in medical diagnostics to analyze the
electrical activity of the heart. However, in clinical practice, these signals are often …
electrical activity of the heart. However, in clinical practice, these signals are often …
Benchmarking of phase locked loop based synchronization techniques for grid-connected inverter systems
Grid-connected renewables are increasingly developed in recent years, eg wind turbine
systems and photovoltaic systems. Synchronization of the injected current with the grid is …
systems and photovoltaic systems. Synchronization of the injected current with the grid is …
Three-phase amplitude adaptive notch filter control design of DSTATCOM under unbalanced/distorted utility voltage conditions
This paper deals with a control design based on amplitude adaptive notch filter (AANF) for a
four-leg distributed static compensator (DSTATCOM) in a three-phase four-wire distribution …
four-leg distributed static compensator (DSTATCOM) in a three-phase four-wire distribution …