Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
The Cauchy problem for the 3D Poisson equation: Landweber iteration vs. horizontally diagonalize and fit method. / Botchev, Mikhail A.; Kabanikhin, Sergey I.; Shishlenin, Maxim A. и др.
в: Journal of Inverse and Ill-Posed Problems, Том 31, № 2, 01.04.2023, стр. 203-221.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - The Cauchy problem for the 3D Poisson equation: Landweber iteration vs. horizontally diagonalize and fit method
AU - Botchev, Mikhail A.
AU - Kabanikhin, Sergey I.
AU - Shishlenin, Maxim A.
AU - Tyrtyshnikov, Eugene E.
PY - 2023/4/1
Y1 - 2023/4/1
N2 - The horizontally diagonalize and fit (HDF) method is proposed to solve the ill-posed Cauchy problem for the three-dimensional Poisson equation with data given on the part of the boundary (a continuation problem). The HDF method consists in discretization over horizontal variables and transformation of the system of differential equations to a diagonal form. This allows to uncouple the original three-dimensional continuation problem into a moderate number of one-dimensional problems in the vertical dimension. The problem size reduction can be carried taking into account the noise level, so that the number k of one-dimensional problems appears to be a regularization parameter. Our experiments show that HDF is applicable to large-scale problems and for n ≤ 2500 is significantly more efficient than Landweber iteration.
AB - The horizontally diagonalize and fit (HDF) method is proposed to solve the ill-posed Cauchy problem for the three-dimensional Poisson equation with data given on the part of the boundary (a continuation problem). The HDF method consists in discretization over horizontal variables and transformation of the system of differential equations to a diagonal form. This allows to uncouple the original three-dimensional continuation problem into a moderate number of one-dimensional problems in the vertical dimension. The problem size reduction can be carried taking into account the noise level, so that the number k of one-dimensional problems appears to be a regularization parameter. Our experiments show that HDF is applicable to large-scale problems and for n ≤ 2500 is significantly more efficient than Landweber iteration.
KW - Continuation problem
KW - inverse and ill-posed problem
KW - regularization
KW - singular values
UR - https://www.scopus.com/inward/record.url?eid=2-s2.0-85147713447&partnerID=40&md5=07a0db71d848ea3408e53d1025f06ecd
UR - https://www.mendeley.com/catalogue/e7c3b01c-94ef-3042-b31e-e46f38a93d6f/
U2 - 10.1515/jiip-2022-0092
DO - 10.1515/jiip-2022-0092
M3 - Article
VL - 31
SP - 203
EP - 221
JO - Journal of Inverse and Ill-Posed Problems
JF - Journal of Inverse and Ill-Posed Problems
SN - 0928-0219
IS - 2
ER -
ID: 50058834