𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Recent Advances in Radial Basis Function Collocation Methods

✍ Scribed by Wen Chen, Zhuo-Jia Fu, C.S. Chen (auth.)


Publisher
Springer-Verlag Berlin Heidelberg
Year
2014
Tongue
English
Leaves
98
Series
SpringerBriefs in Applied Sciences and Technology
Edition
1
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


This book surveys the latest advances in radial basis function (RBF) meshless collocation methods which emphasis on recent novel kernel RBFs and new numerical schemes for solving partial differential equations. The RBF collocation methods are inherently free of integration and mesh, and avoid tedious mesh generation involved in standard finite element and boundary element methods. This book focuses primarily on the numerical algorithms, engineering applications, and highlights a large class of novel boundary-type RBF meshless collocation methods. These methods have shown a clear edge over the traditional numerical techniques especially for problems involving infinite domain, moving boundary, thin-walled structures, and inverse problems.

Due to the rapid development in RBF meshless collocation methods, there is a need to summarize all these new materials so that they are available to scientists, engineers, and graduate students who are interest to apply these newly developed methods for solving real world’s problems. This book is intended to meet this need.

Prof.Wen Chen and Dr.Zhuo-Jia Fu work at Hohai University. Prof. C.S. Chen works at the University of Southern Mississippi.

✦ Table of Contents


Front Matter....Pages i-x
Introduction....Pages 1-4
Radial Basis Functions....Pages 5-28
Different Formulations of the Kansa Method: Domain Discretization....Pages 29-50
Boundary-Type RBF Collocation Methods....Pages 51-87
Open Issues and Perspectives....Pages 89-90

✦ Subjects


Theoretical and Applied Mechanics;Computational Science and Engineering;Numerical and Computational Physics


πŸ“œ SIMILAR VOLUMES


Radial Basis Function Networks 2: New Ad
✍ J. Ghosh, A. Nag (auth.), Dr. Robert J. Howlett, Professor Lakhmi C. Jain (eds.) πŸ“‚ Library πŸ“… 2001 πŸ› Physica-Verlag Heidelberg 🌐 English

<p>The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the

Recent Advances in Iterative Methods
✍ Dianne P. O’Leary (auth.), Gene Golub, Mitchell Luskin, Anne Greenbaum (eds.) πŸ“‚ Library πŸ“… 1994 πŸ› Springer-Verlag New York 🌐 English

<p>This IMA Volume in Mathematics and its Applications RECENT ADVANCES IN ITERATIVE METHODS is based on the proceedings of a workshop that was an integral part of the 1991-92 IMA program on "Applied Linear Algebra. " Large systems of matrix equations arise frequently in applications and they have th