Enhanced multilevel linear sampling methods for inverse scattering problems
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 554-571 |
Journal / Publication | Journal of Computational Physics |
Volume | 257 |
Issue number | PA |
Online published | 16 Oct 2013 |
Publication status | Published - 15 Jan 2014 |
Externally published | Yes |
Link(s)
Abstract
We develop two enhanced techniques for the multilevel linear sampling method (MLSM) proposed in [32] for inverse scattering problems. Under some practical situations, the MLSM suffers certain undesirable "breakage cells" problem. We propose to avoid the curse of "breakage cells" by incorporating "expanding" and "searching" techniques. The new techniques are shown to significantly improve the robustness of the MLSM, and meanwhile they possess the same optimal computational complexity as the MLSM. Numerical experiments are presented to illustrate the promising features of the enhanced MLSMs.
Research Area(s)
- Enhanced multilevel linear sampling method, Inverse scattering problems, Optimal computational complexity
Citation Format(s)
Enhanced multilevel linear sampling methods for inverse scattering problems. / Li, Jingzhi; Liu, Hongyu; Wang, Qi.
In: Journal of Computational Physics, Vol. 257, No. PA, 15.01.2014, p. 554-571.
In: Journal of Computational Physics, Vol. 257, No. PA, 15.01.2014, p. 554-571.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review