Results 41 to 50 of about 1,638 (210)

Numerical solution of fractional differential equations with temporal two-point BVPs using reproducing kernal Hilbert space method

AIMS Mathematics, 2021
In this paper, the reproducing kernel Hilbert space method had been extended to model a numerical solution with two-point temporal boundary conditions for the fractional derivative in the Caputo sense, convergent analysis and error bounds are discussed ...
Yassamine Chellouf, Banan Maayah, Shaher Momani , Ahmad Alawneh, Salam Alnabulsi   +4 more
doaj   +1 more source

Numerical Algorithm for the Third-Order Partial Differential Equation with Three-Point Boundary Value Problem

Abstract and Applied Analysis, 2014
A numerical method based on the reproducing kernel theorem is presented for the numerical solution of a three-point boundary value problem with an integral condition.
Jing Niu, Ping Li
doaj   +1 more source

Simplified iterative reproducing kernel method for handling time-fractional BVPs with error estimation

Ain Shams Engineering Journal, 2018
In this article, we introduce a novel numerical scheme, the iterative reproducing kernel method (IRKM), for providing numerical approximate solutions of a certain class of time-fractional boundary value problem within favorable aspects of the reproducing
Mohammed Al-Smadi
doaj   +1 more source

Some error estimates for the reproducing kernel Hilbert spaces method

Journal of Computational and Applied Mathematics, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Saeid Abbasbandy, Babak Azarnavid
openaire   +1 more source

A Virtual Clinical Trial of Psychedelics to Treat Patients With Disorders of Consciousness

Advanced Science, EarlyView.
Disorders of consciousness after severe brain injury are marked by reduced complexity of brain activity and limited treatment options. Using personalized whole‐brain models, this study shows that simulated lysergic acid diethylamide (LSD) and psilocybin shift patient brain dynamics closer to criticality.
Naji L.N. Alnagger, Paolo Cardone, Charlotte Martial, Yonatan Sanz Perl, Iván Mindlin, Jacobo D Sitt, Leor Roseman, Robin Carhart‐Harris, David Nutt, Pablo Mallaroni, Natasha Mason, Johannes G Ramaekers, Vincent Bonhomme, Steven Laureys, Gustavo Deco, Olivia Gosseries, Pablo Núñez, Jitka Annen   +17 more
wiley   +1 more source

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

Advanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang, Bowen Fu, Chuanchao Zhang, Xiaoping Liu   +3 more
wiley   +1 more source

Numerical technique for solving physical models using reproducing kernel Hilbert space method with purely integral conditions

Boundary Value Problems
In this work, we investigate the Klein–Gordon equation, a physical problem, using the reproducing kernel Hilbert space method (RKHSM). The analytical solution is expressed as a series within the reproducing kernel Hilbert space (RKHS).
Hadjer Zerouali, Nourhane Attia, Ali Akgül, Ahcene Merad, Douha Saadi, Evren Hincal, Murad Khan Hassani   +6 more
doaj   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Density Problem and Approximation Error in Learning Theory

Abstract and Applied Analysis, 2013
We study the density problem and approximation error of reproducing kernel Hilbert spaces for the purpose of learning theory. For a Mercer kernel on a compact metric space (, ), a characterization for the generated reproducing kernel Hilbert space (RKHS)
Ding-Xuan Zhou
doaj   +1 more source

Efficient Dynamics: Reduced‐Order Modeling of the Time‐Dependent Schrödinger Equation

Advanced Physics Research, EarlyView.
Reduced‐order modeling (ROM) approaches for the time‐dependent Schrödinger equation are investigated, highlighting their ability to simulate quantum dynamics efficiently. Proper Orthogonal Decomposition, Dynamic Mode Decomposition, and Reduced Basis Methods are compared across canonical systems and extended to higher dimensions.
Kolade M. Owolabi
wiley   +1 more source