Results 301 to 310 of about 489,759 (365)

Multiresolution reproducing kernel particle methods

Computational Mechanics, 1997
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J. Gosz, Sukky Jun, Wing Kam Liu, Yuli Chen, Wei Hao   +4 more
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Penalized Splines and Reproducing Kernel Methods

The American Statistician, 2006
Two data analytic research areas—penalized splines and reproducing kernel methods—have become very vibrant since the mid-1990s. This article shows how the former can be embedded in the latter via theory for reproducing kernel Hilbert spaces. This connection facilitates cross-fertilization between the two bodies of research.
Pearce, N.D., Wand, M.P.
openaire   +3 more sources

Numerical simulation of time-fractional partial differential equations arising in fluid flows via reproducing Kernel method

International journal of numerical methods for heat & fluid flow, 2019
Purpose The subject of the fractional calculus theory has gained considerable popularity and importance due to their attractive applications in widespread fields of physics and engineering.
O. A. Arqub
semanticscholar   +1 more source

A reproducing kernel method with nodal interpolation property

International Journal for Numerical Methods in Engineering, 2003
AbstractA general formulation for developing reproducing kernel (RK) interpolation is presented. This is based on the coupling of a primitive function and an enrichment function. The primitive function introduces discrete Kronecker delta properties, while the enrichment function constitutes reproducing conditions.
Yang You, Jiun-Shyan Chen, Xueping Meng, Weimin Han   +3 more
openaire   +2 more sources

ON SOME ENRICHMENTS OF REPRODUCING KERNEL PARTICLE METHOD

International Journal of Computational Methods, 2004
In this paper efforts are made to enrich Reproducing Kernel Particle Method (RKPM). Firstly, the RKPM shape functions are expressed explicitly in terms of kernel function moments. This avoids numerical matrix inversions and solutions of linear algebraic equations which are involved in classical RKPM, and thus makes RKPM more accurate, faster and more ...
Zhengliang Zhang, Jinxiong Zhou, Xudong Wang, Lei Zhang   +3 more
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The Reproducing Kernel Method. II

Journal of Mathematical Physics, 1972
The explicit solution of the Cauchy problem ∂N/∂t = HN by means of reproducing kernels is obtained under various forms: conformal mapping expansions, Sheffer polynomial expansion, polynomials orthogonal on a family of curves; the convergence is studied for both Szegö and Bergman kernels.
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Error analysis of the reproducing kernel particle method

Computer Methods in Applied Mechanics and Engineering, 2001
The authors actually discuss a class of projective methods (generalizations of Bubnov-Galerkin methods) with special basis functions associated with the sets of points (quasi-grids) in the closure of the domain. This sets have the parameter \(r>0\). When it tends to zero, the sets (in the given examples) are special grids (only one-dimensional case is ...
Weimin Han, Xueping Meng
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Reproducing kernel particle methods for structural dynamics

International Journal for Numerical Methods in Engineering, 1995
AbstractThis paper explores a Reproducing Kernel Particle Method (RKPM) which incorporates several attractive features. The emphasis is away from classical mesh generated elements in favour of a mesh free system which only requires a set of nodes or particles in space.
Wing Kam Liu, Sukky Jun, Ted Belytschko, Jonathan Adee, Shaofan Li   +4 more
openaire   +3 more sources

Quasi-convex reproducing kernel meshfree method [PDF]

Computational Mechanics, 2014
A quasi-convex reproducing kernel approximation is presented for Galerkin meshfree analysis. In the proposed meshfree scheme, the monomial reproducing conditions are relaxed to maximizing the positivity of the meshfree shape functions and the resulting shape functions are referred as the quasi-convex reproducing kernel shape functions.
Wang, Dongdong, Chen, Pengjie
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Wavelet and multiple scale reproducing kernel methods

International Journal for Numerical Methods in Fluids, 1995
AbstractMultiple scale methods based on reproducing kernel and wavelet analysis are developed. These permit the response of a system to be separated into different scales. These scales can be either the wave numbers corresponding to spatial variables or the frequencies corresponding to temporal variables, and each scale response can be examined ...
Yijung Chen, Wing Kam Liu
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