Numerical differentiation by radial basis functions approximation

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 rules for the regularization parameter, we also give a proof on the convergence error estimate in reconstructing the unknown partial derivatives from scattered noisy data in multi-dimension. Numerical examples verify that the proposed regularization strategy with the a posteriori choice rule is effective and stable to solve the numerical differential problem.

• Type: Journal
• Year: 2007
• Where: ADCM
• Authors: T. Wei, Y. C. Hon
• Keywords: ADCM 2007, Posteriori Choice Rule, Radial Basis Functions, Unknown Partial Derivatives