Computational Mathematics, Algorithms, and Data Processing

• Format: eBook
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: Mathematics and Science; Research and information: general; approximation; Approximation Theory; clustering; constraints; Darcy-Forchheimer model; deep learning; Deep Neural Nets; directional statistics; embedded constraints; finite element method; flow in porous media; generalized multiscale finite element method; heterogeneous media; interpolation; inverse difference; linear multistep methods; mixed generalized multiscale finite element method; multiscale basis functions; multiscale method; multiscale model reduction; native spaces; nonlinear equation; Obrechkoff schemes; polynomial chaos; radial basis functions; ReLU Networks; Rogers-Szegő; second order initial value problems; state estimation; surface modeling; Szegő polynomials; Thiele-like rational interpolation continued fractions with parameters; trigonometrically fitted; truncated function; two-dimensional domain; unattainable point; virtual point
• Online Access: Open Access: DOAB: description of the publication; Open Access: DOAB, download the publication
• Physical Description: 1 online resource (172 p.)
• ISBN: 9783039435913; 9783039435920; books978-3-03943-592-0
• Access: Open 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.