In this paper we study the theoretical limits of finite constructive convex approximations of a given function in a Hilbert space using elements taken from a reduced subset. We also investigate the trade-off between the global error and the partial error during the iterations of the solution. The results obtained constitute a refinement of well-established convergence analysis for constructive iterative sequences in Hilbert spaces with applications in projection pursuit regression and neural network training.
Proceedings European Signal Processing Conference, EUSIPCO, 96
Abdallah, Chaouki T. and D. Docampo. "Bounding the Errors in Constructive Function Approximation." (2012). http://digitalrepository.unm.edu/ece_fsp/41