Computational Mathematics, Algorithms, and Data Processing
Material type:![Article](/opac-tmpl/lib/famfamfam/AR.png)
- books978-3-03943-592-0
- 9783039435913
- 9783039435920
- Research & information: general
- Mathematics & science
- interpolation
- constraints
- embedded constraints
- generalized multiscale finite element method
- multiscale model reduction
- deep learning
- Deep Neural Nets
- ReLU Networks
- Approximation Theory
- radial basis functions
- native spaces
- truncated function
- approximation
- surface modeling
- second order initial value problems
- linear multistep methods
- Obrechkoff schemes
- trigonometrically fitted
- Darcy-Forchheimer model
- flow in porous media
- nonlinear equation
- heterogeneous media
- finite element method
- multiscale method
- mixed generalized multiscale finite element method
- multiscale basis functions
- two-dimensional domain
- Thiele-like rational interpolation continued fractions with parameters
- unattainable point
- inverse difference
- virtual point
- polynomial chaos
- Szegő polynomials
- directional statistics
- Rogers-Szegő
- state estimation
- clustering
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OPJGU Sonepat- Campus | E-Books Open Access | Available |
Open Access star Unrestricted online access
"Computational Mathematics, Algorithms, and Data Processing" of MDPI consists of articles on new mathematical tools and numerical methods for computational problems. Topics covered include: numerical stability, interpolation, approximation, complexity, numerical linear algebra, differential equations (ordinary, partial), optimization, integral equations, systems of nonlinear equations, compression or distillation, and active learning.
Creative Commons https://creativecommons.org/licenses/by/4.0/ cc https://creativecommons.org/licenses/by/4.0/
English
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