Results 51 to 60 of about 5,414 (291)

The meshless analysis of wave equations based on the RRKPM

Results in Physics, 2020
In this paper, the method of radial basis function (RBF) is employed to construct the approximating function of the reproducing kernel particle method (RKPM), which can reduce the adverse effect of different kernel functions on computational accuracy and
Jichao Ma, Hongfen Gao, Gaofeng Wei, Jinwei Qiao   +3 more
doaj   +1 more source

Numerical solvability of generalized Bagley–Torvik fractional models under Caputo–Fabrizio derivative

Advances in Difference Equations, 2021
This paper deals with the generalized Bagley–Torvik equation based on the concept of the Caputo–Fabrizio fractional derivative using a modified reproducing kernel Hilbert space treatment.
Shatha Hasan, Nadir Djeddi, Mohammed Al-Smadi, Shrideh Al-Omari, Shaher Momani, Andreea Fulga   +5 more
doaj   +1 more source

Effective numerical technique for nonlinear Caputo-Fabrizio systems of fractional Volterra integro-differential equations in Hilbert space

Alexandria Engineering Journal, 2022
The point of this paper is to analyze and investigate the analytic-approximate solutions for fractional system of Volterra integro-differential equations in framework of Caputo-Fabrizio operator.
Fatima Youbi, Shaher Momani, Shatha Hasan, Mohammed Al-Smadi   +3 more
doaj   +1 more source

On the Use of Reproducing Kernel Hilbert Spaces in Functional Classification [PDF]

Journal of the American Statistical Association, 2018
The Hájek-Feldman dichotomy establishes that two Gaussian measures are either mutually absolutely continuous with respect to each other (and hence there is a Radon-Nikodym density for each measure with respect to the other one) or mutually singular.
José R. Berrendero, Antonio Cuevas, José L. Torrecilla   +2 more
openaire   +2 more sources

Analytic Kramer kernels, Lagrange-type interpolation series and de Branges spaces

, 2011
The classical Kramer sampling theorem provides a method for obtaining orthogonal sampling formulas. In particular, when the involved kernel is analytic in the sampling parameter it can be stated in an abstract setting of reproducing kernel Hilbert spaces
Hernández-Medina, Miguel A., Miguel A. Hernández-Medina, Antonio G. García, Franciszek Hugon Szafraniec, Hugon Szafraniec, Franciszek, García, Antonio G., Hernández Medina, Miguel Ángel, Szafraniec, Franciszek   +7 more
core   +1 more source

Spheroidal spline interpolation and its application in geodesy

Geodesy and Cartography, 2020
The aim of this paper is to study the spline interpolation problem in spheroidal geometry. We follow the minimization of the norm of the iterated Beltrami-Laplace and consecutive iterated Helmholtz operators for all functions belonging to an appropriate ...
Mostafa Kiani, Nabi Chegini, Abdolreza Safari, Borzoo Nazari   +3 more
doaj   +1 more source

On Weights Which Admit Harmonic Bergman Kernel and Minimal Solutions of Laplace’s Equation

Annales Mathematicae Silesianae, 2022
In this paper we consider spaces of weight square-integrable and harmonic functions L2H(Ω, µ). Weights µ for which there exists reproducing kernel of L2H(Ω, µ) are named ’admissible weights’ and such kernels are named ’harmonic Bergman kernels’. We prove
Żynda Tomasz Łukasz
doaj   +1 more source

Relative reproducing kernel Hilbert spaces [PDF]

, 2014
We introduce a reproducing kernel structure for Hilbert spaces of functions where differences of point evaluations are bounded.
Alpay, Daniel, Volok, Dan, Jorgensen, Palle   +2 more
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source