1977
DOI: 10.1137/0714044
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Practical Approximate Solutions to Linear Operator Equations When the Data are Noisy

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Cited by 698 publications
(402 citation statements)
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“…This is an inherently ill-posed problem and requires some constraints to produce a stable solution. Here we use Tikhonov regularisation [52,53] with the smoothing parameter determined by the Generalized Cross Validation (GCV) method [54,55]. In addition, scanning electron microscopy (SEM) images were acquired to analyse the pore structure.…”
Section: Methodsmentioning
confidence: 99%
“…This is an inherently ill-posed problem and requires some constraints to produce a stable solution. Here we use Tikhonov regularisation [52,53] with the smoothing parameter determined by the Generalized Cross Validation (GCV) method [54,55]. In addition, scanning electron microscopy (SEM) images were acquired to analyse the pore structure.…”
Section: Methodsmentioning
confidence: 99%
“…(5) becomes which should minimize the inner product of Eq. (8) with itself, IIK·f-SII· (10) Unfortunately, these solutions are numerically unstable, because Eq. (8) is ill posed.…”
Section: Conversion To a Fredholm Integral Equation Of Tile First mentioning
confidence: 99%
“…Morozov's discrepancy principle [9], generalized crossvalidation [10], the L-curve method [11]) we want to emphasize the Lepskiibalancing principle [12] which has been shown to be adaptive in the sense that it adapts automatically within a scale of Hilbert spaces in order to select the optimal regularization parameter in a minimax sense. We mention in particular [13] and [14].…”
Section: Introductionmentioning
confidence: 99%