CPL - Chalmers Publication Library
| Utbildning | Forskning | Styrkeområden | Om Chalmers | In English In English Ej inloggad.

Adaptive approximate globally convergent algorithm with backscattered data.

Mohammad Asadzadeh (Institutionen för matematiska vetenskaper, matematik) ; Larisa Beilina (Institutionen för matematiska vetenskaper, matematik)
Inverse Problems and Large-Scale Computations. Springer Proceedings in Mathematics and Statistics. Larisa Beilina, Yury V. Shestopalov (Eds.) (2194-1009). Vol. 52 (2013), p. 1-20.
[Konferensbidrag, refereegranskat]

We construct, analyze and implement an approximately globally convergent finite element scheme for a hyperbolic coefficient inverse problem in the case of backscattering data. This extends the computational aspects introduced in Asadzadeh and Beilina (Inv. Probl. 26, 115007, 2010), where using Laplace transformation, the continuous problem is reduced to a nonlinear elliptic equation with a gradient dependent nonlinearity. We investigate the behavior of the nonlinear term and discuss the stability issues as well as optimal a posteriori error bounds, based on an adaptive procedure and due to the maximal available regularity of the exact solution. Numerical implementations justify the efficiency of adaptive a posteriori approach in the globally convergent setting.

Denna post skapades 2013-12-13. Senast ändrad 2014-10-09.
CPL Pubid: 189177


Läs direkt!

Länk till annan sajt (kan kräva inloggning)

Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematik (2005-2016)



Chalmers infrastruktur