Article information
2021 , Volume 26, ¹ 2, p.72-87
Shumilov B.M.
On splitting for cubic spline wavelets with four zero moments on an interval
The article examines the problem of constructing a splitting algorithm for cubic spline wavelets. First, a cubic spline space is constructed for splines with homogeneous Dirichlet boundary conditions. Then, using the first four zero moments, the corresponding wavelet space is constructed. The resulting space consists of cubic spline wavelets that satisfy the orthogonality conditions for all thirddegree polynomials. The originality of the research lies in obtaining implicit relations connecting the coefficients of the spline expansion at the initial level with the spline coefficients and wavelet coefficients at the embedded level by a band system of linear algebraic equations with a nondegenerate matrix. Excluding the even rows of the system, the resulting transformation algorithm is obtained as a solution to a sequence of band systems of linear algebraic equations with five (instead of three in the case of two zero moments) diagonals. The presence of strict diagonal dominance over the columns is proved, which confirms the stability of the computational process. For comparison, we adopt the results of calculations using wavelets orthogonal to first-degree polynomials and interpolating cubic spline wavelets with the property of the best mean-square approximation of the second derivative of the function being approximated. The results of numerical experiments show that the scheme with four zero moments is more accurate in the approximation of functions, but becomes inferior in accuracy to the approximation of the second derivative
[full text] [link to elibrary.ru]
Keywords: B-splines, wavelets, implicit decomposition relation
doi: 10.25743/ICT.2021.26.2.006
Author(s): Shumilov Boris Mihailovich Dr. , Professor Position: Professor Office: Tomsk State University of Architecture and Building Address: 634003, Russia, Tomsk, Solyanaya square, 2
Phone Office: (382) 2417689 E-mail: sbm@tsuab.ru SPIN-code: 4445-9076 References: 1. Chui C.K. An introduction to wavelets. N.Y., London: Academic Press; 1992: 366.
2. Stollnitz E.J., DeRose T.D., Salesin D.H. Wavelets for computer graphics. San Francisco: Morgan Kaufmann Publishers; 1996: 290.
3. Frazier M.W. An introduction to wavelets through linear algebra. N.Y.: Springer Verlag; 1999: 596.
4. Lyche T., Mørken K., Quak E. Theory and algorithms for non-uniform spline wavelets. Multivariate approximation and applications. Cambridge: Cambridge University Press; 2001: 152–187.
5. Cohen A., Daubechies I., Feauveau J.-C. Biorthogonal bases of compactly supported wavelets. Communications on Pure and Applied Mathematics. 1992; (45):485–560.
6. Wang J. Cubic spline wavelet bases of Sobolev spaces and multilevel interpolation. Applied and Computational Harmonic Analysis. 1996; 3(2):154–163.
7. Koro K., Abe K. Non-orthogonal spline wavelets for boundary element analysis. Engineering Analysis with Boundary Elements. 2001; (25):149–164.
8. Shumilov B.M. Splitting algorithms for the wavelet transform of first-degree splines on nonuniform grids. Computational Mathematics and Mathematical Physics. 2016; 56(7):1209–1219.
9. Shumilov B.M. Splitting algorithm for cubic spline-wavelets with two vanishing moments on the interval. Siberian Electronic Mathematical Reports. 2020; (17):2105–2121. DOI:10.33048/semi.2020.17.141. (In Russ.)
10. Zav’yalov Yu.S., Kvasov B.I., Miroshnichenko V.L. Metody splayn-funktsiy [Methods of splinefunctions]. Moscow: Nauka; 1980: 352. (In Russ.)
11. Bubnova N.V. Wavelet-Galerkin method for numerical simulation of thin-wire antennas. Computational Technologies. 2008; 13(Spest.vypusk 4):12–19. (In Russ.)
12. Cerna D. Cubic spline wavelets with four vanishing moments on the interval and their applications to option pricing under Kou mode. International Journal of Wavelets, Multiresolution and Information Processing. 2019; 17(1):1850061.
13. Samarskii A.A., Nikolaev E.S. Numerical methods for grid equations, vol. I: Direct methods. Basel: Birkhauser; 1989: 242.
14. Shumilov B.M. Cubic multiwavelets orthogonal to polynomials and a splitting algorithm. Numerical Analysis and Applications. 2013; 6(3):247–259.
15. Pissanetzky S. Sparse matrix technology. London: Academic Press; 1984: 321.
16. Cerna D., Finek V. Cubic spline wavelets with short support for fourth-order problems. Applied Mathematics and Computation. 2014; (243):44–56.
17. Shumilov B.M. Semi-orthogonal spline-wavelets with derivatives and the algorithm with splitting. Numerical Analysis and Applications. 2017; 10(1):90–100. Bibliography link: Shumilov B.M. On splitting for cubic spline wavelets with four zero moments on an interval // Computational technologies. 2021. V. 26. ¹ 2. P. 72-87
|