On increasing stability in an inverse source problem with local boundary data at many wave numbers

2020 ◽  
pp. 1-13
Author(s):  
Victor Isakov
2006 ◽  
Vol 85 (10) ◽  
pp. 1219-1243 ◽  
Author(s):  
M. Bellassoued ◽  
D. Jellali ◽  
M. Yamamoto

2006 ◽  
Vol 47 (3) ◽  
pp. 397-411
Author(s):  
C. N. Anestopoulos ◽  
E. E. Argyropoulos

AbstractWe examine the transmission problem in a two-dimensional domain, which consists of two different homogeneous media. We use boundary integral equation methods on the Maxwell equations governing the two media and we study the behaviour of the solution as the two different wave numbers tend to zero. We prove that as the boundary data of the general transmission problem converge uniformly to the boundary data of the corresponding electrostatic transmission problem, the general solution converges uniformly to the electrostatic one, provided we consider compact subsets of the domains.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Oleg Y. Imanuvilov ◽  
Yavar Kian ◽  
Masahiro Yamamoto

Abstract For a parabolic equation in the spatial variable x = ( x 1 , … , x n ) {x=(x_{1},\ldots,x_{n})} and time t, we consider an inverse problem of determining a coefficient which is independent of one spatial component x n {x_{n}} by lateral boundary data. We apply a Carleman estimate to prove a conditional stability estimate for the inverse problem. Also, we prove similar results for the corresponding inverse source problem.


1989 ◽  
Vol 98 (3) ◽  
pp. 639-657 ◽  
Author(s):  
E. P. van den Ban ◽  
H. Schlichtkrull

2021 ◽  
pp. 125-139
Author(s):  
Abdalkaleg Atia Idris Hamad

This paper examines extensions of an iterative method for inverse evaluation of the source function for two elliptic systems. The method begins with a starting value for the undetermined source. Next, a background field and equations for the error field are obtained. 2-D domains are considered. This method is suitable for Helmholtz and Poisson operators. In the presence of finite-difference grid resolution, a varying amount of boundary data, and methods of filtering the noise in the boundary data and the noise intensity of the boundary data, the performance, accuracy, and iteration count of the algorithm are investigated. Keywords: Source, Inverse Problems, Poisson, Noise, Ill-Posedness, Well-Posed


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