Search Results for "radial basis function"

The STK is a (not so) Small Toolbox for Kriging. Its primary focus in on the interpolation / regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior. The STK also provides tools for the sequential and non-sequential design of experiments. Even though it is, currently, mostly geared towards the Design and Analysis of Computer Experiments (DACE), the STK can be useful for other applications areas (such as Geostatistics, Machine Learning, Non-parametric Regression, etc.).

Matrix factorization is applied to the B-spline basis to construct an orthonormal basis. Data can be approximated by a linear combination of the orthonormal basis functions. Constraints are imposed such that the fitted function is linear at the boundary points, as in natural cubic spline.

The extended finite element method (XFEM) classified, one of the partition of unity method (PUM), allows discontinuities to be simulated independently of the mesh. This is possible by adding appropriate functions to the FE approximation basis, for example, the Heaviside function. The discontinuities can evolve in time, without a need for a conforming mesh. A MATLAB implementation of the XFEM written by VP Nguyen, is given here. The interaction of cracks and crack-inclusion interaction is modelled with XFEM framework. The elements intersected by discontinuity surface are sub-divided into quadrature subcells aligned with the discontinuity and higher order quadrature is adopted. ...