Univariate fuzzy-random neural network approximation operators
In this article, we study the rate of pointwise convergence in the q-mean to thefuzzy-random unit operator of very precise univariate fuzzy-random neural network operators of cardaliaguet-Euvrard and "squashing" types. These fuzzy-random operators arise in a natural and common way among fuzzy-random neural networks. These rates are given through probabilistic Jackson type inequalities involving the fuzzy-random modulus of continuity of the engaged fuzzy-random function or its fuzzy derivatives. Also several interesting new results in fuzzy-random analysis are given of independent merit, which are used then in the proofs of the main results of the paper. © 2004 Elsevier Ltd. All rights reserved.
Computers and Mathematics with Applications
Anastassiou, G. (2004). Univariate fuzzy-random neural network approximation operators. Computers and Mathematics with Applications, 48 (9), 1263-1283. https://doi.org/10.1016/j.camwa.2004.10.020