COMPUTATIONAL COMPLEXITY IN WORST, STOCHASTIC AND AVERAGE CASE SETTING ON FUNCTIONAL APPROXIMATION PROBLEM OF MULTIVARIATE

摘要

The order of computational complexity of all bounded linear functional approximation problem is determined for the generalized Sobolev class Wp∧(Id), Nikolskii class Hk∞(Id) in the worst (deterministic), stochastic and average case setting, from which it is concluded that the bounded linear functional approximation problem for the classes stochastic and average case setting.