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E., Meshfree Approximation Methods with MATLAB, Mathematical Sciences, World Scientific Publishers, Singapore, volume 6, (2007).

D., Radial basis functions: theory and Cambridge implementations, (2003). Zhu, A new meshless local Petrov-Galerkin (MLPG) approach in computational mechanics, Comput. Krysl, Meshless methods: An overview and recent developments, Comput.

S., Solitons: an introduction, Cambridge University Press (1989). De Marchi, Nonstandard Kernels and their Applications, Dolomites Research Notes on Approximation 2, (2009) (http: drna.di.). Marchi, and Plonka-Hoch, editors, Kernel Functions and Meshless Methods, volume 4 of Dolomites Research Notes on Approximation, Special Issue. E., Positive definite kernels: Past, present and future. Used as class notes for graduate courses at Northwestern University, Illinois Institute of Technology, and Vanderbilt University, this book will appeal to both mathematics and engineering graduate students. A good balance is supplied between the necessary theory and implementation in terms of many MATLAB programs, with examples and applications to illustrate key points. Meshfree approximation methods, such as radial basis function and moving least squares method, are discussed from a scattered data approximation and partial differential equations point of view. The emphasis here is on a hands-on approach that includes MATLAB routines for all basic operations. Whereas other works focus almost entirely on theoretical aspects or applications in the engineering field, this book provides the salient theoretical results needed for a basic understanding of meshfree approximation methods. Meshfree approximation methods are a relatively new area of research, and there are only a few books covering it at present. Approximation of Point Cloud Data in 3D.Compactly Supported Radial Basis Functions.Miscellaneous Theory: Other Norms and Scattered Data Fitting on Manifolds.