Decomposition and Regularization of the Solution of Ill-Conditioned Inverse Problems in Processing of Measurement Information. Part 1. A Theoretical Evalution of the Method
A theoretical evaluation of a method of solving ill-conditioned inverse problems that arise in mathematicostatistical processing of measurement information under conditions of unavoidable errors in measurements and a mathematical model of the study object is considered. The method is based on physic...
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| Veröffentlicht in: | Measurement techniques 2018-06, Vol.61 (3), p.223-231 |
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| container_title | Measurement techniques |
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| creator | Surnin, Yu. V. |
| description | A theoretical evaluation of a method of solving ill-conditioned inverse problems that arise in mathematicostatistical processing of measurement information under conditions of unavoidable errors in measurements and a mathematical model of the study object is considered. The method is based on physical and canonical decomposition of the initial model of the object, specified in the form of a system of linear equations as well as two-sided regularization of the solution of a canonical (diagonal) system of equations. It is shown that through the use of the method it is possible to create an adaptive algorithm for recognition and stable estimation of a group of information parameters of a physically decomposed model. |
| doi_str_mv | 10.1007/s11018-018-1413-6 |
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| subjects | Adaptive algorithms Analytical Chemistry Characterization and Evaluation of Materials Conditioning Decomposition Inverse problems Linear equations Mathematical models Measurement Science and Instrumentation Physical Chemistry Physics Physics and Astronomy Regularization |
| title | Decomposition and Regularization of the Solution of Ill-Conditioned Inverse Problems in Processing of Measurement Information. Part 1. A Theoretical Evalution of the Method |
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