Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
Rotating machinery fault-induced vibration signal modulation effects: A review with mechanisms, extraction methods and applications for diagnosis
Rotating machinery faults can induce characteristic modulation effects in a vibration signal,
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
[HTML][HTML] Deep learning in food category recognition
Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …
research for the past few decades. It is potentially one of the next steps in revolutionizing …
[图书][B] Transforms and applications handbook
AD Poularikas, AM Grigoryan - 2018 - taylorfrancis.com
Updating the original, Transforms and Applications Handbook, Third Edition solidifies its
place as the complete resource on those mathematical transforms most frequently used by …
place as the complete resource on those mathematical transforms most frequently used by …
Deep fractional Fourier transform
Existing deep learning-based computer vision methods usually operate in the spatial and
frequency domains, which are two orthogonal\textbf {individual} perspectives for image …
frequency domains, which are two orthogonal\textbf {individual} perspectives for image …
Open access dataset, toolbox and benchmark processing results of high-density surface electromyogram recordings
We provide an open access dataset of High densitY Surface Electromyogram (HD-sEMG)
Recordings (named “Hyser”), a toolbox for neural interface research, and benchmark results …
Recordings (named “Hyser”), a toolbox for neural interface research, and benchmark results …
LT-SEI: Long-tailed specific emitter identification based on decoupled representation learning in low-resource scenarios
H Zha, H Wang, Z Feng, Z Xiang, W Yan… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In the case of COVID-19, which requires stable and reliable tracking of personnel
movement, aircraft identification by specific emitter identification (SEI) is a hot-button issue. It …
movement, aircraft identification by specific emitter identification (SEI) is a hot-button issue. It …
Short-time fractional Fourier transform and its applications
R Tao, YL Li, Y Wang - IEEE Transactions on Signal Processing, 2009 - ieeexplore.ieee.org
The fractional Fourier transform (FRFT) is a potent tool to analyze the chirp signal. However,
it fails in locating the fractional Fourier domain (FRFD)-frequency contents which is required …
it fails in locating the fractional Fourier domain (FRFD)-frequency contents which is required …
Localizing damage on stainless steel structures using acoustic emission signals and weighted ensemble regression-based convolutional neural network
Nuclear power generation is an essential part of the electrical supply in the United States,
and it is an effective way to achieve low carbon power generation. Nuclear power …
and it is an effective way to achieve low carbon power generation. Nuclear power …
Short-time Fourier transform with the window size fixed in the frequency domain
C Mateo, JA Talavera - Digital Signal Processing, 2018 - Elsevier
Abstract The Short-Time Fourier Transform (STFT) is widely used to convert signals from the
time domain into a time–frequency representation. This representation has well-known …
time domain into a time–frequency representation. This representation has well-known …