In this paper, approximation by linear combinations of an increasing number n of computational units with adjustable parameters (such as perceptrons and radial basis functions) is ...
Radial basis functions (RBFs) have found important applications in areas such as signal processing, medical imaging, and neural networks since the early 1980's. Several appli...
Abstract. We present a new derivative-free algorithm, ORBIT, for unconstrained local optimization of computationally expensive functions. A trust-region framework using interpolati...
Stefan M. Wild, Rommel G. Regis, Christine A. Shoe...
We introduce a master–worker framework for parallel global optimization of computationally expensive functions using response surface models. In particular, we parallelize two r...
Facial Motion Cloning (FMC) is the technique employed to transfer the motion of a virtual face (namely the source) to a mesh representing another face (the target), generally havi...
Marco Fratarcangeli, Marco Schaerf, Robert Forchhe...
We study cubature formulas on relatively small scattered samples in the unit square, obtained by integrating radial basis function (RBF) interpolants. Numerical tests show that, d...
We suggest a local hybrid approximation scheme based on polynomials and radial basis functions, and use it to modify the scattered data fitting algorithm of [7]. Similar to that a...
Based on radial basis functions approximation, we develop in this paper a new computational algorithm for numerical differentiation. Under an a priori and an a posteriori choice r...
In this paper we analyse a hybrid approximation of functions on the sphere S2 R3 by radial basis functions combined with polynomials, with the radial basis functions assumed to be...
It is often observed that interpolation based on translates of radial basis functions or non-radial kernels is numerically unstable due to exceedingly large condition of the kerne...