Discrete approximation by variational vector splines for noisy data
The authors deal with the problem of constructing and/or approximating a curve or surface from a scattered data set. Their purpose is to adapt the theory of the discrete variational splines relative to sets of data perturbed by a random noise in order to obtain an almost sure convergence for these splines. They also present some numerical and graphical examples in order to prove the efficiency of the method.
scientific article; zbMATH DE number 5610220
scientific article