Results 21 to 30 of about 101,252 (223)
DIAS: A Data-Informed Active Subspace Regularization Framework for Inverse Problems
Computation, 2022 This paper presents a regularization framework that aims to improve the fidelity of Tikhonov inverse solutions. At the heart of the framework is the data-informed regularization idea that only data-uninformed parameters need to be regularized, while the ...
Hai Nguyen +2 more
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A new interpretation of (Tikhonov) regularization [PDF]
Inverse Problems, 2021 Abstract Tikhonov regularization with square-norm penalty for linear forward operators has been studied extensively in the literature. However, the results on convergence theory are based on technical proofs and sometimes difficult to interpret.
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Intelligent Particle Swarm Optimization Method for Parameter Selecting in Regularization Method for Integral Equation [PDF]
BIO Web of ConferencesWe 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. +5 more
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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
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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
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Bayesian regularization: From Tikhonov to horseshoe [PDF]
WIREs Computational Statistics, 2019 Bayesian regularization is a central tool in modern‐day statistical and machine learning methods. Many applications involve high‐dimensional sparse signal recovery problems. The goal of our paper is to provide a review of the literature on penalty‐based regularization approaches, from Tikhonov (Ridge, Lasso) to horseshoe regularization.This article is ...
Polson, Nicholas G., Sokolov, Vadim
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Tikhonov Regularization and Total Least Squares [PDF]
SIAM Journal on Matrix Analysis and Applications, 1999 The regularized total least squares (TLS) method of the TLS problem is introduced and its regularizing properties are studied. It is also proved that, in certain cases, the new method is superior to standard regularization methods.
Gene H. Golub +2 more
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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 +4 more
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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
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On the convergence of algorithms with Tikhonov regularization terms [PDF]
Optimization Letters, 2020 We consider the strongly convergent modified versions of the Krasnosel'ski\uı-Mann, the forward-backward and the Douglas-Rachford algorithms with Tikhonov regularization terms, introduced by Radu Boţ, Ernö Csetnek and Dennis Meier. We obtain quantitative information for these modified iterations, namely rates of asymptotic regularity and metastability.
Bruno Dinis, Pedro Pinto 0003
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