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...
Radial basis function networks (RBF) are efficient general function approximators. They show good generalization performance and they are easy to train. Due to theoretical consider...
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...
Background: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for par...
Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibilit...