High Order Multivariate Fuzzy Approximation by Neural Network Operators Based on The Error Function

摘要

Here are studied in terms of multivariate fuzzy high approximation to the multivariate unit sequences of multivariate fuzzy error function based neural network operators. These operators are multivariate fuzzy analogs of earlier considered multivariate real ones. The derived results generalize earlier real ones into the fuzzy level. Here the high order multivariate fuzzy pointwise and uniform convergences with rates to the multivariate fuzzy unit operator are given through multivariate fuzzy Jackson type inequalities involving the multivariate fuzzy moduli of continuity of the mth order (m > 0) H -fuzzy partial derivatives, of the involved multivariate fuzzy number valued function. The treated operators are of quasi-interpolation, Kantorovich and quadrature types at the multivariate fuzzy setting.