A reconstruction of object properties with significant uncertainties. Issue 3 (4th March 2021)

• Record Type: Journal Article
• Authors: Romanovski, M.
• Is Part Of: Inverse problems in science and engineering. Volume 29:Issue 3(2021)
• Page Start: 318
• Page End: 364
• Publication Date: 2021-03-04
• Subjects: Simulation -- experimental data -- mathematical model -- parameter estimation -- identifiability -- regularization -- locally sequential refinement; 35K05 -- 35R30 -- 65J20 -- 65R30 -- 65N21; Engineering mathematics -- Periodicals; Inverse problems (Differential equations) -- Periodicals; 620.001515357
• DOI: 10.1080/17415977.2020.1782900
• Languages: English
• ISSNs: 1741-5977

Abstract

ABSTRACT: An approach is developed to read and simulate experimental data using inverse problems. The idea is founded on a locally sequential refinement of the reconstruction. The regularization that occurs under a scheme of separate matching with observations is the basis for a numerical solution. The simultaneous identification of several unknowns using a set of mathematical models and functional representations of the desired quantities combines the simulation with inverse problem solutions. This unified approach is applied to the investigation of the enzyme kinetics. The object in question is simulated in the absence of information about the functional type of sought kinetic parameters, the noise structure and its level, and also details of observations. Nevertheless, the composition and volume of the samples under consideration prove to be sufficient not only for determining all of the kinetic parameters but also for clarifying the observation conditions. The obtained results demonstrate the effectiveness of the sequential regularized solutions to the inverse problems for the case of acting at once all the known features of ill-posed problems.