Results 41 to 50 of about 90,750 (294)
On Quasi-interpolation with Radial Basis Functions
Journal of Approximation Theory, 1993 The author shows that infinite linear combinations of translates of radial functions can be defined that provide polynomial exactness in spaces whose dimensions are not restricted to a prescribed parity as it was usually assumed. Complete proofs as well as comments and references are presented along the paper.
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CURVATURE BASED CHARACTERIZATION OF RADIAL BASIS FUNCTIONS: APPLICATION TO INTERPOLATION
Mathematical Modelling and Analysis, 2023 Choosing the scale or shape parameter of radial basis functions (RBFs) is a well-documented but still an open problem in kernel-based methods. It is common to tune it according to the applications, and it plays a crucial role both for the accuracy and stability of the method.
Mohammad Heidari +2 more
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A modified radial basis function interpolation method for aerodynamic load application
Hangkong gongcheng jinzhanAerodynamic loads are an important type of load in finite element analysis of aircraft structures. Due to the mismatch between the mesh used in computational fluid dynamics（CFD）and the one in structural analysis， and the load can be given in the form of ...
ZHENG Wei, XIONG Jun, LIU Jian, JI Kai
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IEEE Access, 2017 An improved full-wave multilevel Green's function interpolation method (MLGFIM) with RBF-QR technique is proposed for the fast evaluation of electromagnetic field.
Peng Zhao, Chi Hou Chan, Gaofeng Wang
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Computation of transient viscous flows using indirect radial basis function networks [PDF]
, 2007 In this paper, an indirect/integrated radial-basis-function network (IRBFN) method is further developed to solve transient partial differential equations (PDEs) governing fluid flow problems.
Mai-Cao, Lan +2 more
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Analytical formulas for polynomial coefficients in radial basis function interpolation
Mathematical Modelling and AnalysisRadial basis functions (RBF) are used in many areas, including interpolation and approximation, solution of partial differential equations, neural networks, and machine learning. RBFs are based on the sum of weighted kernel functions.
Vaclav Skala
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Ain Shams Engineering Journal, 2016 In this paper, the meshless local radial point interpolation (MLRPI) method is applied to one-dimensional inverse heat conduction problems. The meshless LRPIM is one of the truly meshless methods since it does not require any background integration cells.
Elyas Shivanian +1 more
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A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller
International Journal of Adaptive Control and Signal Processing, EarlyView.Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg +5 more
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The Matlab Radial Basis Function Toolbox
Journal of Open Research Software, 2017 Radial Basis Function (RBF) methods are important tools for scattered data interpolation and for the solution of Partial Differential Equations in complexly shaped domains.
Scott A. Sarra
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Partition of unity interpolation using stable kernel-based techniques [PDF]
, 2016 In this paper we propose a new stable and accurate approximation technique which is extremely effective for interpolating large scattered data sets.
Cavoretto, R. +4 more
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