What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Algebra
- Algorithm
Mathematical analysis, Applied mathematics, Algorithm, Integral equation and Numerical analysis are his primary areas of study.
His Mathematical analysis research is multidisciplinary, relying on both Visualization and Galerkin method.
His work carried out in the field of Applied mathematics brings together such families of science as Space, Wavelet and Petrov–Galerkin method.
His Algorithm study combines topics in areas such as Numerical range, Image denoising, Convex function, Mathematical optimization and Continuous wavelet transform.
His Convex function research integrates issues from Convex conjugate, Norm, Noise reduction and Linear map.
The various areas that he examines in his Integral equation study include Rate of convergence, Iterated function, Iterative method and Superconvergence.
His most cited work include:
- Gearbox fault diagnosis using empirical mode decomposition and Hilbert spectrum (266 citations)
- Universal Kernels (262 citations)
- A B-spline approach for empirical mode decompositions (209 citations)
What are the main themes of his work throughout his whole career to date?
Yuesheng Xu mostly deals with Algorithm, Mathematical analysis, Applied mathematics, Mathematical optimization and Integral equation.
His research ties Norm and Algorithm together.
As a part of the same scientific study, Yuesheng Xu usually deals with the Mathematical analysis, concentrating on Galerkin method and frequently concerns with Numerical integration.
His Applied mathematics research also works with subjects such as
- Nonlinear system most often made with reference to Wavelet,
- Linear system that intertwine with fields like Coefficient matrix.
In general Integral equation, his work in Volterra integral equation is often linked to Orthogonal collocation linking many areas of study.
His biological study spans a wide range of topics, including Fixed point and Convex optimization.
He most often published in these fields:
- Algorithm (51.12%)
- Mathematical analysis (33.96%)
- Applied mathematics (27.61%)
What were the highlights of his more recent work (between 2015-2021)?
- Algorithm (51.12%)
- Fixed point (8.58%)
- Iterative reconstruction (7.46%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Algorithm, Fixed point, Iterative reconstruction, Artificial intelligence and Optimization problem.
Yuesheng Xu combines subjects such as Image processing, Norm and Mathematical optimization with his study of Algorithm.
His research investigates the connection between Fixed point and topics such as Minification that intersect with issues in Two stage algorithm.
His biological study spans a wide range of topics, including Image quality, Image resolution, Deblurring, Imaging phantom and Noise reduction.
He has researched Optimization problem in several fields, including Rate of convergence, Convex function, Least squares and Convex optimization.
The subject of his Numerical analysis research is within the realm of Mathematical analysis.
Between 2015 and 2021, his most popular works were:
- Multiplicative noise removal in imaging: An exp-model and its fixed-point proximity algorithm (27 citations)
- Noisy 1-bit compressive sensing: Models and algorithms (21 citations)
- Wavelet inpainting with the ℓ0 sparse regularization (16 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Algebra
- Algorithm
Yuesheng Xu spends much of his time researching Algorithm, Iterative reconstruction, Mathematical optimization, Multiplicative noise and Reduction.
His research in Algorithm is mostly focused on Regularization.
His studies in Iterative reconstruction integrate themes in fields like Penalty method, Single-photon emission computed tomography, Mean squared error, Imaging phantom and Image noise.
His study looks at the relationship between Mathematical optimization and fields such as Image quality, as well as how they intersect with chemical problems.
The various areas that he examines in his Reduction study include Polynomial, Piecewise linear function, Discrete system, Integral equation and Piecewise.
His Convex function research is multidisciplinary, incorporating perspectives in Optimization problem, Fixed point and Rate of convergence.
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