Larisa Beilina

Prof. Larisa Beilina

orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2012
Verified
Book
Closed access
LBLarisa Beilina
Larisa Beilina
MKMichael Victor Klibanov
Michael Victor Klibanov

20 May 2010 in Journal of Mathematical Sciences
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Journal Article
Closed access
PDF file
LBLarisa Beilina
Larisa Beilina
MKM. V. Klibanov
M. V. Klibanov
MKM. Yu. Kokurin
M. Yu. Kokurin

14 August 2012 in Inverse Problems
Verified
Journal Article
Closed access
AKAndrey V Kuzhuget
Andrey V Kuzhuget
UTUNCC/ChalmersGU team
UNCC/ChalmersGU team
LBLarisa Beilina
Larisa Beilina
MKMichael V Klibanov
Michael V Klibanov
ASAnders Sullivan
Anders Sullivan
MFMichael Fiddy
Michael Fiddy

1 January 2015 in SIAM Journal on Imaging Sciences
Verified
Journal Article
Closed access
NTNguyen Trung Thành
Nguyen Trung Thành
LBLarisa Beilina
Larisa Beilina
MKMichael V. Klibanov
Michael V. Klibanov
MFMichael A. Fiddy
Michael A. Fiddy
We consider the problem of imaging of objects buried under the ground using experimental backscattering time-dependent measurements generated by a single point source or one incident plane wave. In particular, we estimate dielectric constants of these objects using the globally convergent inverse algorithm of Beilina and Klibanov. Our algorithm is tested on experimental data collected using a microwave scattering facility at the University of North Carolina at Charlotte. There are two main challenges in working with this type of experimental data: (i) there is a huge misfit between these data and computationally simulated data, and (ii) the signals scattered from the targets may overlap with and be dominated by the reflection from the ground's surface. To overcome these two challenges, we propose new data preprocessing steps to make the experimental data look similar to the simulated data, as well as to remove the reflection from the ground's surface. Results of a total of 25 data sets of both nonblind and blind targets indicate good accuracy.

1 January 2005 in Mathematical Models and Methods in Applied Sciences
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Journal Article
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PDF file
LBLarisa Beilina
Larisa Beilina
CJClaes Johnson
Claes Johnson

1 April 2015 in Nonlinear Analysis: Real World Applications
Verified
Journal Article
Closed access
LBLarisa Beilina
Larisa Beilina
MKMichael V. Klibanov
Michael V. Klibanov