Results 21 to 30 of about 24,593 (203)

Intelligent Particle Swarm Optimization Method for Parameter Selecting in Regularization Method for Integral Equation [PDF]

BIO Web of Conferences
We use the Tikhonov method as a regularization technique for solving the integral equation of the first kind with noisy and noise-free data. Following that, we go over how to choose the Tikhonov regularization parameter by implementing the Intelligent ...
Al-Mahdawi H.K., Hatem Khorsheed Farah, Subhi Alhumaima Ali, Ramadhan Ali J., Hussien Kilan M, Alkattan Hussein   +5 more
doaj   +1 more source

Arnoldi–Tikhonov regularization methods

Journal of Computational and Applied Mathematics, 2009
The problem is to solve a large, ill-conditioned linear system \(Ax=b\) of size \(n\), where \(b=\hat{b}+e\) with \(\hat{b}\) the ``true'' vector and \(e\) some error. Tikhonov regularization minimizes \(\|Ax-b\|^2+\mu^{-1}\|x\|\) with \(\mu\) a regularization parameter.
Lewis, Bryan, Reichel, Lothar
openaire   +1 more source

An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations

Advances in Multimedia, 2014
To avoid the staircase artifacts, an adaptive image denoising model is proposed by the weighted combination of Tikhonov regularization and total variation regularization.
Kui Liu, Jieqing Tan, Benyue Su
doaj   +1 more source

Regularization matrices determined by matrix nearness problems [PDF]

, 2016
This paper is concerned with the solution of large-scale linear discrete ill-posed problems with error-contaminated data. Tikhonov regularization is a popular approach to determine meaningful approximate solutions of such problems.
Brezinski, Calvetti, Calvetti, Calvetti, Donatelli, Donatelli, Dykes, Eldén, Engl, Gazzola, Guangxin Huang, Hansen, Hansen, Hansen, Kindermann, Lewis, Lothar Reichel, Morigi, Neuman, Noschese, Phillips, Reichel, Reichel, Silvia Noschese   +23 more
core   +2 more sources

An Adjoint‐Free Alternating Direction Method for Four‐Dimensional Variational Data Assimilation With Multiple Parameter Tikhonov Regularization

Earth and Space Science, 2020
Tikhonov regularization is critical for accurately specifying both the background (B) and observational (R) error covariances in four‐dimensional variational data assimilation (4DVar). The ratio of the background and observation error variances (referred
Xiangjun Tian, Rui Han, Hongqin Zhang
doaj   +1 more source

Ozone profile smoothness as a priori information in the inversion of limb measurements [PDF]

Annales Geophysicae, 2004
In this work we discuss inclusion of a priori information about the smoothness of atmospheric profiles in inversion algorithms. The smoothness requirement can be formulated in the form of Tikhonov-type regularization, where the smoothness of ...
V. F. Sofieva, J. Tamminen, H. Haario, E. Kyrölä, M. Lehtinen   +4 more
doaj   +1 more source

Reconstruction of Mercury's internal magnetic field beyond the octupole [PDF]

Annales Geophysicae, 2022
The reconstruction of Mercury's internal magnetic field enables us to take a look into the inner heart of Mercury. In view of the BepiColombo mission, Mercury's magnetosphere is simulated using a hybrid plasma code, and the multipoles of the internal ...
S. Toepfer, I. Oertel, V. Schiron, Y. Narita, Y. Narita, K.-H. Glassmeier, K.-H. Glassmeier, D. Heyner, P. Kolhey, U. Motschmann, U. Motschmann   +10 more
doaj   +1 more source

Multidirectional Subspace Expansion for One-Parameter and Multiparameter Tikhonov Regularization [PDF]

, 2016
Tikhonov regularization is a popular method to approximate solutions of linear discrete ill-posed problems when the observed or measured data is contaminated by noise.
C Brezinski, C Groetsch, CC Paige, D Calvetti, D Fong, GH Golub, Ian N. Zwaan, J Lampe, K Kunisch, L Reichel, L Reichel, L Reichel, M Belge, M Fornasier, ME Hochstenbach, ME Hochstenbach, ME Kilmer, Michiel E. Hochstenbach, P Perona, PC Hansen, PC Hansen, RC Li, S Gazzola, S Lu, S Lu   +24 more
core   +3 more sources

Spatially Adaptive Tensor Total Variation-Tikhonov Model for Depth Image Super Resolution

IEEE Access, 2017
Depth images play an important role in 3-D applications. However, due to the limitation of depth acquisition equipment, the acquired depth images are usually in limited resolution. In this paper, a spatially adaptive tensor total variation-Tikhonov model
Gang Zhong, Sen Xiang, Peng Zhou, Li Yu
doaj   +1 more source

An Exponential Filtering Based Inversion Method for Microwave Imaging [PDF]

Radioengineering, 2021
In this paper, a new methodology based on the exponential filtering of singular values is adopted to solve the linear ill-posed problem of microwave imaging.
A. Magdum, M. Erramshetty, R. P. K. Jagannath   +2 more
doaj