[1]
|
A. Buccini, G. Huang and L. Reichel, On the choice of regularization matrix for an $\ell_ 2-\ell_q$ minimization method for image restoration, Appl. Numer. Math., 164 (2021), 211-221.
doi: 10.1016/j.apnum.2020.11.004.
|
[2]
|
A. Buccini and L. Reichel, An $\ell_ 2-\ell_q$ regularization method for large discrete ill-posed problems, J. Sci. Comput., 78 (2019), 1526-1549.
doi: 10.1007/s10915-018-0816-5.
|
[3]
|
D. Calvetti and L. Reichel, Tikhonov regularization of large linear problems, BIT Numer. Math., 43 (2003), 263-283.
doi: 10.1023/A:1026083619097.
|
[4]
|
J. Cornelis, N. Schenkels and W. Vanroose, Projected Newton method for noise constrained Tikhonov regularization, Inverse. Probl., 36 (2020), 055002, 28 pp.
doi: 10.1088/1361-6420/ab7d2b.
|
[5]
|
J. Cornelis and W. Vanroose, Projected Newton method for noise constrained $\ell_p$ regularization, Inverse. Probl., 36 (2020), 125004, 32 pp.
doi: 10.1088/1361-6420/abb2fc.
|
[6]
|
M. Donatelli, A. Neuman and L. Reichel, Square regularization matrices for large linear discrete ill-posed problems, Numer. Linear. Algebr., 19 (2012), 896-913.
doi: 10.1002/nla.1833.
|
[7]
|
L. Dykes, G. Huang, S. Noschese and L. Reichel, Regularization matrices for discrete ill-posed problems in several space-dimensions, Numer. Linear Algebr., 25 (2018), 1-16.
doi: 10.1002/nla.2163.
|
[8]
|
S. Gazzola, P. Novati and M. R. Russo, On Krylov projection methods and Tikhonov regularization, Electron. Trans. Numer. Anal, 44 (2015), 83-123.
|
[9]
|
S. Gazzola, E. Onunwor and L. Reichel, On the Lanczos and Golub-Kahan reduction methods applied to discrete ill-posed problems, Numer. Linear. Algebr., 23 (2016), 187-204.
doi: 10.1002/nla.2020.
|
[10]
|
P. C. Hansen, Regularization tools version 4.0 for Matlab 7.3, Numer. Algorithms, 46 (2007), 189-194.
doi: 10.1007/s11075-007-9136-9.
|
[11]
|
P. C. Hansen, Discrete Inverse Problems: Insight and Algorithms, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2010.
doi: 10.1137/1.9780898718836.
|
[12]
|
P. C. Hansen, Rank-Deficient and Discrete Ill-posed Problems: Numerical Aspects of Linear Inversion, SIAM Monographs on Mathematical Modeling and Computation. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 1998.
doi: 10.1137/1.9780898719697.
|
[13]
|
M. E. Hochstenbach and L. Reichel, An iterative method for Tikhonov regularization with a general linear regularization operator, J. Integral. Equ. Appl., 22 (2010), 465-482.
doi: 10.1216/JIE-2010-22-3-465.
|
[14]
|
G. Huang, A. Lanza and S. Morigi, Majorization minimization generalized Krylov subspace methods for $\ell_p-\ell_q$ optimization applied to image restoration, BIT Numer. Math., 57 (2017), 351-378.
doi: 10.1007/s10543-016-0643-8.
|
[15]
|
G. Huang, L. Reichel and F. Yin, Projected nonstationary iterated Tikhonov regularization, BIT Numer. Math., 56 (2016), 467-487.
doi: 10.1007/s10543-015-0568-7.
|
[16]
|
J. Lampe, L. Reichel and H. Voss, Large-scale Tikhonov regularization via reduction by orthogonal projection, Linear. Algebra. Appl., 436 (2012), 2845-2865.
doi: 10.1016/j.laa.2011.07.019.
|
[17]
|
A. Lanza, S. Morigi, L. Reichel and F. Sgallari, A generalized Krylov subspace method for $\ell_p-\ell_q$ minimization, SIAM J. Sci. Comput., 37 (2015), 30-50.
doi: 10.1137/140967982.
|
[18]
|
P. Novati and M. R. Russo, Adaptive Arnoldi-Tikhonov regularization for image restoration, Numer. Algorithms, 65 (2014), 745-757.
doi: 10.1007/s11075-013-9712-0.
|