5 papers · 1 filter
Results, challenges and new steps on RBF approximation and computation
Stefano De Marchi, Nadaniela Egidi, Josephin Giacomini +1
We present an up-to-date overview of approximation methods based on Radial Basis Function (RBF) techniques, which have recently attracted attention across various computational too…
A Note on the Direct Approximation of Derivatives in Rational Radial Basis Functions Partition of Unity Method
Vahid Mohammadi, Stefano De Marchi
This paper proposes a Direct Rational Radial Basis Functions Partition of Unity (D-RRBF-PU) approach to compute derivatives of functions with steep gradients or discontinuities. Th…
On the Lebesgue constant of the Morrow-Patterson points
Tomasz Beberok, Leokadia BiaÅas-Cież, Stefano De Marchi
The study of interpolation nodes and their associated Lebesgue constants are central to numerical analysis, impacting the stability and accuracy of polynomial approximations. In th…
Fast-Decaying Polynomial Reproduction
Stefano De Marchi, Giacomo Cappellazzo
Polynomial reproduction plays a relevant role in deriving error estimates for various approximation schemes. Local reproduction in a quasi-uniform setting is a significant factor i…
-convergence of Kantorovich-type Max-Min Neural Network Operators
Ä°smail Aslan, Stefano De Marchi, Wolfgang Erb
In this work, we study the Kantorovich variant of max-min neural network operators, in which the operator kernel is defined in terms of sigmoidal functions. Our main aim is to demo…