A collocation method for Fredholm integral equations of the first kind via iterative regularization scheme
Abstract
To solve the ill-posed integral equations, we use the regularized collocation method. This numerical method is a combination of the Legendre polynomials with non-stationary iterated Tikhonov regularization with fixed parameter. A theoretical justification of the proposed method under the required assumptions is detailed. Finally, numerical experiments demonstrate the efficiency of this method.
Keywords:
ill-posed problems, iterative regularization scheme, Legendre collocation method, integral equations of the first kindHow to Cite
Share
License
Copyright (c) 2023 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
C. Canuto, M.Y. Hussaini, A. Quarteroni and T.A. Zang. Spectral methods: fundamentals in single domains. Springer Science & Business Media, 2007. https://doi.org/10.1007/978-3-540-30726-6"> https://doi.org/10.1007/978-3-540-30726-6
Z. Chen, S. Cheng, G. Nelakanti and H. Yang. A fast multiscale Galerkin method for the first kind ill-posed integral equations via Tikhonov regularization. International Journal of Computer Mathematics, 87(3):565–582, 2010. https://doi.org/10.1080/00207160802155302"> https://doi.org/10.1080/00207160802155302
M. Donatelli. On nondecreasing sequences of regularization parameters for nonstationary iterated Tikhonov. Numerical Algorithms, 60(4):651–668, 2012.
H.W. Engl, M. Hanke and A. Neubauer. Regularization of inverse problems, volume 375. Springer Science & Business Media, 1996.
L. Fanchun, Y. Suhua, L. Xingjun and P. Yubing. Multilevel iterative algorithm for solving Fredholm integral equation of the first kind. Mathematica Numerica Sinica, 35(3):225–238, 2013. https://doi.org/10.12286/jssx.2013.3.225"> https://doi.org/10.12286/jssx.2013.3.225
U. Hamarik, E. Avi and A. Ganina. On the solution of ill-posed problems by projection methods with a posteriori choice of the discretization level. Mathematical Modelling and Analysis, 7(2):241–252, 2002. https://doi.org/10.3846/13926292.2002.9637196"> https://doi.org/10.3846/13926292.2002.9637196
M. Hanke and C.W. Groetsch. Nonstationary iterated Tikhonov regularization. Journal of Optimization Theory and Applications, 98(1):37–53, 1998. https://doi.org/10.1023/A:1022680629327"> https://doi.org/10.1023/A:1022680629327
G. Huang, L. Reichel and F. Yin. Projected nonstationary iterated Tikhonov regularization. BIT Numerical Mathematics, 56(2):467–487, 2016. https://doi.org/10.1007/s10543-015-0568-7"> https://doi.org/10.1007/s10543-015-0568-7
A.V. Kryanev. An iterative method for solving incorrectly posed problems. USSR Computational Mathematics and Mathematical Physics, 14(1):24–35, 1974. https://doi.org/10.1016/0041-5553(74)90133-5"> https://doi.org/10.1016/0041-5553(74)90133-5
S. Lu and S.V. Pereverzev. Regularization theory for ill-posed problems. de Gruyter, Berlin, Boston, 2013. https://doi.org/10.1515/9783110286496"> https://doi.org/10.1515/9783110286496
Y. Lu, L. Shen and Y. Xu. Multi-parameter regularization methods for high-resolution image reconstruction with displacement errors. IEEE Transactions on Circuits and Systems I: Regular Papers, 54(8):1788–1799, 2007. https://doi.org/10.1109/TCSI.2007.902535"> https://doi.org/10.1109/TCSI.2007.902535
X. Luo, L. Fan, Y. Wu and F. Li. Fast multi-level iteration methods with compression technique for solving ill-posed integral equations. Journal of Computational and Applied Mathematics, 256:131–151, 2014. https://doi.org/10.1016/j.cam.2013.07.043"> https://doi.org/10.1109/TCSI.2007.902535
M.T. Nair. Linear operator equations: approximation and regularization. World Scientific, 2009.
M.T. Nair. Quadrature based collocation methods for integral equations of the first kind. Advances in Computational Mathematics, 36(2):315–329, 2012. https://doi.org/10.1007/s10444-011-9196-1"> https://doi.org/10.1007/s10444-011-9196-1
M.T. Nair and S.V. Pereverzev. Regularized collocation method for Fredholm integral equations of the first kind. Journal of Complexity, 23(4):454–467, 2007. https://doi.org/10.1016/j.jco.2006.09.002"> https://doi.org/10.1016/j.jco.2006.09.002
B. Neggal, N. Boussetila and F. Rebbani. Projected Tikhonov regularization method for Fredholm integral equations of the first kind. Journal of Inequalities and Applications, 2016(195):1–21, 2016. https://doi.org/10.1186/s13660-016-1137-6"> https://doi.org/10.1186/s13660-016-1137-6
B. Nemati Saray. Sparse multiscale representation of Galerkin method for solving linear-mixed Volterra-Fredholm integral equations. Mathematical Methods in the Applied Sciences, 43(5):2601–2614, 2020. https://doi.org/doi.org/10.1002/mma.6068"> https://doi.org/doi.org/10.1002/mma.6068
T. Poggio and C.R. Shelton. On the mathematical foundations of learning. Bulletin of the American Mathematical Society, 39(1):1–49, 2002. https://doi.org/10.1090/S0273-0979-01-00923-5"> https://doi.org/10.1090/S0273-0979-01-00923-5
A. Quarteroni and A. Valli. Numerical approximation of partial differential equations, volume 23. Springer Science & Business Media, 2008.
M.P. Rajan. A modified convergence analysis for solving Fredholm integral equations of the first kind. Integral Equations and Operator Theory, 49(4):511– 516, 2004. https://doi.org/10.1007/s00020-002-1213-9"> https://doi.org/10.1007/s00020-002-1213-9
B. Tahar, B. Nadjib and R. Faouzia. A variant of projection regularization method for ill-posed linear operator equations. International Journal of Computational Methods, 18(04):2150008, 2021. https://doi.org/10.1142/S0219876221500080"> https://doi.org/10.1142/S0219876221500080
J. Thomas King and D. Chillingworth. Approximation of generalized inverses by iterated regularization. Numerical Functional Analysis and Optimization, 1(5):499–513, 1979. https://doi.org/10.1080/01630567908816031"> https://doi.org/10.1080/01630567908816031
C.R. Vogel and M.E. Oman. Fast, robust total variation-based reconstruction of noisy, blurred images. IEEE transactions on image processing, 7(6):813–824, 1998. https://doi.org/10.1109/83.679423"> https://doi.org/10.1109/83.679423
S. Yang, X. Luo, F. Li and G. Long. A fast multiscale Galerkin method for the first kind ill-posed integral equations via iterated regularization. Applied Mathematics and Computation, 219(21):10527–10537, 2013. https://doi.org/10.1016/j.amc.2013.04.029"> https://doi.org/10.1016/j.amc.2013.04.029
View article in other formats
Published
Issue
Section
Copyright
Copyright (c) 2023 The Author(s). Published by Vilnius Gediminas Technical University.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.