—This paper aims to develop a novel framework to systematically trade-off computational complexity with output distortion in linear multimedia transforms, in an optimal manner. T...
Abstract. Radial basis function (RBF) approximation is an extremely powerful tool for representing smooth functions in non-trivial geometries, since the method is meshfree and can ...
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 derive differential equations for evolving radial basis functions (RBFs) to solve segmentation problems. The differential equations result from applying variation...
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...