| تعداد نشریات | 32 |
| تعداد شمارهها | 856 |
| تعداد مقالات | 8,306 |
| تعداد مشاهده مقاله | 52,806,770 |
| تعداد دریافت فایل اصل مقاله | 9,238,954 |
Radial polynomials as alternatives to flat radial basis functions | ||
| Journal of Mathematical Modeling | ||
| مقاله 10، دوره 12، شماره 2، مهر 2024، صفحه 337-354 اصل مقاله (541.32 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2024.26001.2304 | ||
| نویسندگان | ||
| Fatemeh Pooladi؛ hosseinzadeh Hosseinzadeh* | ||
| Department of Mathematics, Persian Gulf University, Bushehr, Iran | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Smooth radial basis function؛ radial polynomial؛ Numerical approximation؛ Interpolation | ||
| مراجع | ||
|
[1] D. Chen, Research on traffic flow prediction in the big data environment based on the improved RBF neural network, IEEE Trans. Ind. Inform. 13 (2017) 2000–2008. [2] T.A. Driscoll, B. Fornberg, Interpolation in the limit of increasingly flat radial basis functions, Comput. Math. Appl. 43 (2002) 413–422. [3] G.E. Fasshauer, Meshfree Approximation Methods with MATLAB, World Scientific, 2007. [4] B. Fornberg, N. Flyer, A Primer on Radial basis Functions with Applications to the Geosciences, SIAM, 2015. [5] B. Fornberg, E. Larsson, N. Flyer, Stable computations with Gaussian radial basis functions, SIAM J. Sci. Comput. 33 (2011) 869–892. [6] B. Fornberg, E. Lehto, C. Powell, Stable calculation of Gaussian-based RBF-FD stencils, Comput. Math. Appl. 65 (2013) 627–637. [7] B. Fornberg, C. Piret, A stable algorithm for flat radial basis functions on a sphere, SIAM J. Sci. Comput. 30 (2007) 60–80. [8] B. Fornberg, G. Wright, Stable computation of multiquadric interpolants for all values of the shape parameter, Comput. Math. Appl. 48 (2004) 853–867. [9] B. Fornberg, G. Wright, E. Larsson, Some observations regarding interpolants in the limit of flat radial basis functions, Comput. Math. Appl. 47 (2004) 37–55. [10] B. Fornberg, J. Zuev, The Runge phenomenon and spatially variable shape parameters in RBF interpolation, Comput. Math. Appl. 54 (2007) 379–398. [11] P. Gonzalez-Rodriguez, M. Moscoso, M. Kindelan, Laurent expansion of the inverse of perturbed, singular matrices, J. Comput. Phys. 299 (2015) 307–319. [12] R. L. Hardy, Multiquadric equations of topography and othephysical research, 76 (1971) 1905–1915. [13] M.K. Esfahani, A. Neisy, S. De Marchi, An RBF approach for oil futures pricing under the jump- diffusion model, J. Math. Model. 9 (2021) 81–92. [14] E. Larsson, B. Fornberg. Theoretical and computational aspects of multivariate interpolation with increasingly flat radial basis functions, Comput. Math. Appl. 49 (2005) 103–130. [15] W.R. Madych, Miscellaneous error bounds for multiquadric and related interpolators, Comput. Math. Appl. 24 (1992) 121–138. [16] M. Mongillo, Choosing basis functions and shape parameters for radial basis function methods, SIAM undergraduate research online, 4 (2011) 190–209. [17] R. Schaback, Error estimates and condition numbers for radial basis function interpolation, Adv. Comput. Math. 3 (1995) 251–264. [18] R. Schaback, Multivariate interpolation by polynomials and radial basis functions, Constr. Approx. 21 (2005) 293–317. [19] F. Soleymani, Sh. Zhu. Error and stability estimates of a time-fractional option pricing model under fully spatial-temporal graded meshes, J. Comput. Appl. Math. 425 (2023) 115075. [20] H. Wendland, Scattered Data Approximation, Cambridge University Press, 2004. [21] G. B. Wright, B. Fornberg, Stable computations with flat radial basis functions using vector-valued rational approximations, J. Comput. Phys. 331 (2017) 137–156. [22] Y. Wu, X. Sun, Optimization and simulation of enterprise management resource scheduling based on the radial basis function (RBF) neural network, Comput. Intell. Neurosci. 2021 (2021) 6025492 | ||
|
آمار تعداد مشاهده مقاله: 493 تعداد دریافت فایل اصل مقاله: 445 |
||