What is he best known for?
The fields of study Xuefeng Chen is best known for:
- Hilbert–Huang transform
- Time–frequency analysis
- Wavelet
Xuefeng Chen frequently studies issues relating to Artificial intelligence and Pattern recognition (psychology).
As part of his studies on Artificial intelligence, Xuefeng Chen often connects relevant areas like Pattern recognition (psychology).
While working in this field, Xuefeng Chen studies both Fault (geology) and Seismology.
His work often combines Seismology and Fault (geology) studies.
He combines Algorithm and Computer vision in his studies.
Xuefeng Chen undertakes multidisciplinary investigations into Computer vision and Algorithm in his work.
In his works, he conducts interdisciplinary research on Mathematical optimization and Lagrange multiplier.
Xuefeng Chen merges many fields, such as Lagrange multiplier and Mathematical optimization, in his writings.
His research on Nuclear magnetic resonance frequently links to adjacent areas such as Stacking.
His most cited work include:
- Sparsity-enabled signal decomposition using tunable Q-factor wavelet transform for fault feature extraction of gearbox (168 citations)
- Nonconvex Sparse Regularization and Convex Optimization for Bearing Fault Diagnosis (153 citations)
- An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder (133 citations)
What are the main themes of his work throughout his whole career to date
Xuefeng Chen is involved in relevant fields of research such as Minimax, Penalty method and Minification in the realm of Mathematical optimization.
His study ties his expertise on Mathematical optimization together with the subject of Minification.
Many of his studies involve connections with topics such as Feature extraction and Artificial intelligence.
While working on this project, Xuefeng Chen studies both Seismology and Fault (geology).
In his research, he undertakes multidisciplinary study on Fault (geology) and Seismology.
His Pattern recognition (psychology) study frequently involves adjacent topics like Artificial intelligence.
Xuefeng Chen regularly links together related areas like Sparse approximation in his Algorithm studies.
Much of his study explores Sparse approximation relationship to Algorithm.
He integrates many fields, such as Programming language and SIGNAL (programming language), in his works.
Xuefeng Chen most often published in these fields:
- Artificial intelligence (91.30%)
- Seismology (60.87%)
- Fault (geology) (60.87%)
What were the highlights of his more recent work (between 2020-2022)?
- Artificial intelligence (100.00%)
- Quantum mechanics (50.00%)
- Operating system (50.00%)
In recent works Xuefeng Chen was focusing on the following fields of study:
Xuefeng Chen links relevant scientific disciplines such as Classifier (UML) and Test data in the realm of Programming language.
His Classifier (UML) study frequently intersects with other fields, such as Programming language.
In his works, he undertakes multidisciplinary study on Artificial intelligence and Test set.
His Calibration research extends to Quantum mechanics, which is thematically connected.
His work on Calibration is being expanded to include thematically relevant topics such as Quantum mechanics.
His Operating system study frequently draws connections between related disciplines such as Encoder.
Xuefeng Chen performs integrative Encoder and Rotary encoder research in his work.
His research brings together the fields of Operating system and Rotary encoder.
Xuefeng Chen connects Optics with Grating in his research.
Between 2020 and 2022, his most popular works were:
- Deep-Learning-Based Open Set Fault Diagnosis by Extreme Value Theory (29 citations)
- A survey on the grating based optical position encoder (8 citations)
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