Theoretical and Numerical Approximation Through Generalized Fractional Integral Type Max Product Neural Network Operators
Abstract
In this paper, we define a nonlinear extension of the fractional sum-type neural network operators of Kadak et al. [Citation1] using the max-product approach. Also, we introduce multivariate generalized max fractional neural network-type operators of order α>0. The quantitative estimates of operators are analyzed using the multivariate modulus of continuity and absolute moments. Finally, we provide illustrative examples, along with graphs and error tables, that show the excellent accuracy of the operators when using the chosen activation functions.
Fields of Study & Subjects
Neural Networks and Applications
Fractional Differential Equations Solutions
Approximation Theory and Sequence Spaces
Publication details
- Journal / source
- Numerical Functional Analysis and Optimization
- Publisher
- Informa UK Limited
- Volume
- 47
- Issue
- 1-6
- Pages
- 3–29
- Publication date
- 24 March 2026
- Language
- EN