Amanote Research

Amanote Research

    RegisterSign In

Approximation by Perturbed Neural Network Operators

Applicationes Mathematicae
doi 10.4064/am42-1-5
Full Text
Open PDF
Abstract

Available in full text

Date

January 1, 2015

Authors
George A. Anastassiou
Publisher

Institute of Mathematics, Polish Academy of Sciences


Related search

Approximation by Max-Product Operators

Fasciculi Mathematici
2018English

Weighted Approximation by Baskakov Operators

Mathematical Inequalities and Applications
MathematicsApplied Mathematics
2015English

Statistical Approximation by Positive Linear Operators

Studia Mathematica
Mathematics
2004English

Design of Hybrid Fuzzy Neural Network for Function Approximation

Journal of Intelligent Learning Systems and Applications
2010English

On Spectral Properties of Perturbed Operators

Proceedings of the American Mathematical Society
MathematicsApplied Mathematics
1995English

Upper Approximation Operators Induced by Alexandrov Fuzzy Topologies

International Journal of Pure and Applied Mathematics
MathematicsApplied Mathematics
2014English

Approximation by Szász Type Operators Including Sheffer Polynomials

Journal of Mathematics and Applications
2017English

Approximation by (P,q)-Analogue of Balázs-Szabados Operators

Filomat
Mathematics
2018English

Universal Approximation to Nonlinear Operators by Neural Networks With Arbitrary Activation Functions and Its Application to Dynamical Systems

IEEE Transactions on Neural Networks
1995English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy