1983
DOI: 10.1007/bf01254725
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Methods of solving ill-posed inverse problems

Abstract: A number of methods of solving inverse heat-conduction problems are analyzed from the point of view of their practical use. Problems of determining discrepancy gradients and obtaining smooth solutions are considered as applied to the method of iteration regularization.i. At the present time there exist two directions in the study of effects of heat and mass transfer, viz., the active development of methods of numerical modeling on the basis of equations expressing conservation laws, and continual improvement o… Show more

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Cited by 45 publications
(52 citation statements)
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“…This is discussed in more detail later. The regularization method we use is generally called Tikhonov [20][21][22] regularization. Typically, the functional B involves some measures of smoothness that derive from ÿrst or higher derivatives.…”
Section: Whole-ÿeld Deconvolution For Multiple Forcesmentioning
confidence: 99%
“…This is discussed in more detail later. The regularization method we use is generally called Tikhonov [20][21][22] regularization. Typically, the functional B involves some measures of smoothness that derive from ÿrst or higher derivatives.…”
Section: Whole-ÿeld Deconvolution For Multiple Forcesmentioning
confidence: 99%
“…In the TSVD, high-frequency oscillation due to errors in the input data are filtered out by the truncation of lowest singular values of the considered linear operator (for further reference, see [11,12]). Traditionally, in the Tikhonov method the solution is obtained by minimizing the smoothing functional [13][14][15][16]:…”
Section: Introductionmentioning
confidence: 99%
“…An effective method for determining the gradient is the introduction of the conjugate boundary value problem [2] ,...…”
mentioning
confidence: 99%