Due to the high approximation power and simplicity of computation of smooth radial basis functions (RBFs), in recent decades they have received much attention for function approximation. These RBFs contain a shape parameter that regulates their approximation power and stability but its optimal selection is challenging. To avoid this difficulty, this paper follows a novel and computationally efficient strategy to propose a space of radial polynomials with even degree that well approximates flat RBFs. The proposed space, $\mathcal{H}_n$, is the shifted radial polynomials of degree $2n$. By obtaining the dimension of $\mathcal{H}_n$ and introducing a basis set, it is shown that $\mathcal{H}_n$ is considerably smaller than $\mathcal{P}_{2n}$ while the distances from RBFs to both $\mathcal{H}_n$ and $\mathcal{P}_{2n}$ are nearly equal. For computation, by introducing new basis functions, two computationally efficient approaches are proposed. Finally, the presented theoretical studies are verified by the numerical results.
Pooladi, F., & Hosseinzadeh, H. (2024). Radial polynomials as alternatives to flat radial basis functions. Journal of Mathematical Modeling, 12(2), 337-354. doi: 10.22124/jmm.2024.26001.2304
MLA
Fatemeh Pooladi; hosseinzadeh Hosseinzadeh. "Radial polynomials as alternatives to flat radial basis functions". Journal of Mathematical Modeling, 12, 2, 2024, 337-354. doi: 10.22124/jmm.2024.26001.2304
HARVARD
Pooladi, F., Hosseinzadeh, H. (2024). 'Radial polynomials as alternatives to flat radial basis functions', Journal of Mathematical Modeling, 12(2), pp. 337-354. doi: 10.22124/jmm.2024.26001.2304
VANCOUVER
Pooladi, F., Hosseinzadeh, H. Radial polynomials as alternatives to flat radial basis functions. Journal of Mathematical Modeling, 2024; 12(2): 337-354. doi: 10.22124/jmm.2024.26001.2304