High-order fuzzy approximation by fuzzywavelet type and neural network operators
Abstract
Here are studied, in terms of fuzzy high approximation to the unit, several basic sequences of fuzzy wavelet type operators and fuzzy neural network operators. These operators are fuzzy analogs of earlier studied real ones. The produced results generalize earlier real ones into the fuzzy setting. Here, the high-order fuzzy pointwise convergence with rates to the fuzzy unit operator is established through fuzzy inequalities involving the fuzzy modulus of continuity of the Nth-order (N < 1) H-fuzzy derivative of the engaged fuzzy number valued function. At the end, we present a related Lp result for fuzzy neural network operators. © 2004 Elsevier Ltd. All rights reserved.
Publication Title
Computers and Mathematics with Applications
Recommended Citation
Anastassiou, G. (2004). High-order fuzzy approximation by fuzzywavelet type and neural network operators. Computers and Mathematics with Applications, 48 (9), 1387-1401. https://doi.org/10.1016/j.camwa.2004.10.028
