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...
Networks estimating probability density are usually based on radial basis function of the same type. Feature Space Mapping constructive network based on separable functions, optimi...
Wlodzislaw Duch, Rafal Adamczak, Geerd H. F. Dierc...
This paper presents a fast algorithm for smooth digital elevation model interpolation and approximation from scattered elevation data. The global surface is reconstructed by subdi...
Joachim Pouderoux, Jean-Christophe Gonzato, Ireneu...
Procedural encoding of scattered and unstructured scalar datasets using Radial Basis Functions (RBF) is an active area of research with great potential for compactly representing ...
Manfred Weiler, Ralf P. Botchen, Simon Stegmaier, ...
This paper shows that scattered range data can be smoothed at low cost by fitting a Radial Basis Function (RBF) to the data and convolving with a smoothing kernel (low pass filt...
Jonathan C. Carr, Richard K. Beatson, Bruce C. McC...