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An Improved Tikhonov Regularization Method for Conductivity Tomography Imaging
2008 International Symposium on Computer Science and Computational Technology, 2008Discretizations of inverse problem lead to systems of linear equations with a highly ill-conditioned coefficient matrix, and in order to compute stable solutions to these systems it is necessary to apply regularization methods. This paper compares our improved Tikhonov regularization algorithm to several existing regularization methods, which are ...
Baobin Feng, Wenjuan Wang, Junxing Cao
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Tomosar Focusing by Means of A Variant of Tikhonov Regularized Method
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019Tomographic synthetic aperture radar (TomoSAR) imaging has shown great potential in the three dimensional SAR focusing in recent years. One practical challenge is that the spatial separation of the multi-pass system is always nonuniform and also the number of tracks is very limited, thus leading to the focusing results inaccurate. Conventional Tikhonov
Jinwei Xie, Zhibin Wang, Zhenfang Li
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Tikhonov regularization methods for inverse variational inequalities
Optimization Letters, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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An adaptive Tikhonov regularization method for fluorescence molecular tomography
Medical & Biological Engineering & Computing, 2013The high degree of absorption and scattering of photons propagating through biological tissues makes fluorescence molecular tomography (FMT) reconstruction a severe ill-posed problem and the reconstructed result is susceptible to noise in the measurements.
Xu Cao +6 more
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On Krylov projection methods and Tikhonov regularization [PDF]
, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gazzola S, Novati P, Russo M.R.
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jiip, 1998
The Tikhonov regularization method for the operator equation \(Tu=f\) with an injective linear closed operator in Banach spaces is considered. The method consists in minimization of the functional \[ \| Tu-f_\delta\| ^p+\alpha\| Lu\| ^q \] on \(D(T)\cap D(L)\), for some linear closed operator \(L\) and \(\alpha>0\), \(p>1\), \(q>1\).
Menikhes, L. D., Tanana, V. P.
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The Tikhonov regularization method for the operator equation \(Tu=f\) with an injective linear closed operator in Banach spaces is considered. The method consists in minimization of the functional \[ \| Tu-f_\delta\| ^p+\alpha\| Lu\| ^q \] on \(D(T)\cap D(L)\), for some linear closed operator \(L\) and \(\alpha>0\), \(p>1\), \(q>1\).
Menikhes, L. D., Tanana, V. P.
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Tikhonov Regularization Methods for Variational Inequality Problems
Journal of Optimization Theory and Applications, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Tikhonov Regularization Method for Image Reconstruction
1993Many problems of image reconstruction from projection data have the following mathematical form $$ Am = d $$ (1) where m is the unknown model, d is the observed data and A is a known operator. If A is independent of the model m, the tomographic problem is linear; otherwise it is nonlinear.
Chengbin Peng +2 more
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Tikhonov Regularization Methods for the Inverse Scalp Electroencephalography
Volume 2: Biomedical and Biotechnology Engineering, 2009Electroencephalography (EEG) source localization of brain activity is of high diagnostic value. Noninvasive numerical procedures can be developed to help reconstruct the cortical brain activities from the low-spatial-resolution scalp EEG measurement.
Menglu Wu, Xiaolin Chen
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Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2002
This paper presents a systematic and computable method for choosing the regularization parameter appearing in Tikhonov-type regularization based on non-quadratic regularizers. First, we extend the notion of the L-curve, originally defined for quadratically regularized problems, to the case of non-quadratic functions. We then associate the optimal value
Soontorn Oraintara +3 more
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This paper presents a systematic and computable method for choosing the regularization parameter appearing in Tikhonov-type regularization based on non-quadratic regularizers. First, we extend the notion of the L-curve, originally defined for quadratically regularized problems, to the case of non-quadratic functions. We then associate the optimal value
Soontorn Oraintara +3 more
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