Scattered Noisy Data Fitting Using Bivariate Splines

Abstract

Abstract In this paper, we present a extension of weighted least squares method to fit the Hermite scattered data with noise. This method is different from the method in [1] which can only deal with the Lagrange scattered data. We give some numerical experiments to show the performance of our method. In addition, suppose the number of noisy data is large enough and the noisy term has the uniform distribution on interval [−1,1], we show that the error bound can get better by average the coefficients of several splines which are constructed by fitting different sets of data.