Abstract
This paper deals with the determination of the rate of convergence to the unit of perturbed Kantorovich–Choquet univariate and multivariate normalized neural network operators of one hidden layer. These are given through the univariate and multivariate moduli of continuity of the involved univariate or multivariate function or its high order derivatives and that appears in the right-hand side of the associated univariate and multivariate Jackson type inequalities. The activation function is very general, especially it can derive from any univariate or multivariate sigmoid or bell-shaped function. The right hand sides of our convergence inequalities do not depend on the activation function. The sample functionals are of Kantorovich–Choquet type. We give applications for the first derivatives of the involved function.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Revista de la Real Academia de Ciencias Exactas, Físicas y Naturales. Serie A. Matemáticas
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.