D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Mathematics D-index 33 Citations 4,947 165 World Ranking 1621 National Ranking 700

Overview

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.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Universal Kernels

Charles A. Micchelli;Yuesheng Xu;Haizhang Zhang.
The Journal of Machine Learning Research archive (2006)

450 Citations

Gearbox fault diagnosis using empirical mode decomposition and Hilbert spectrum

B. Liu;S. Riemenschneider;Y. Xu.
Mechanical Systems and Signal Processing (2006)

414 Citations

A B-spline approach for empirical mode decompositions

Qiuhui Chen;Norden E. Huang;Sherman D. Riemenschneider;Yuesheng Xu.
Advances in Computational Mathematics (2006)

366 Citations

Proximity algorithms for image models: denoising

Charles A. Micchelli;Charles A. Micchelli;Lixin Shen;Yuesheng Xu;Yuesheng Xu.
Inverse Problems (2011)

210 Citations

Wavelet analysis and applications

Icwaa;Tao Qian;Mang I Vai;Yuesheng Xu.
(2007)

178 Citations

Using the Matrix Refinement Equation for the Construction of Wavelets on Invariant Sets

Charles A. Micchelli;Yuesheng Xu.
Applied and Computational Harmonic Analysis (1994)

177 Citations

Deterministic convergence of an online gradient method for BP neural networks

Wei Wu;Guorui Feng;Zhengxue Li;Yuesheng Xu.
IEEE Transactions on Neural Networks (2005)

158 Citations

Two-dimensional empirical mode decomposition by finite elements

Y Xu;B Liu;J Liu;S Riemenschneider.
Proceedings of The Royal Society A: Mathematical, Physical and Engineering Sciences (2006)

128 Citations

Reproducing Kernel Banach Spaces for Machine Learning

Haizhang Zhang;Yuesheng Xu;Jun Zhang.
Journal of Machine Learning Research (2009)

126 Citations

Gauss-type quadratures for weakly singular integrals and their application to Fredholm integral equations of the second kind

Hideaki Kaneko;Yuesheng Xu.
Mathematics of Computation (1994)

122 Citations

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