Abstract
The problem of mathematical interpretation of experimental data is considered for distributed parameter systems with the use of models supposed to be adequate to the objects under study. Theoretical foundations are developed for linear systems on the basis of Green functions. They allow formulating various inverse problems associated with the interpretation problem. Regularization procedures that make it possible to find approximate solutions consistent with errors in available data are recommended and described. In this connection, representation of the class of models as decompositions that asymptotically approximate to the exact description is important. Constructive algorithms to solve interpretation problem are given.
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*Continued from Cybernetics and Systems Analysis, Vol. 55, No. 2, 220–231 (2019).
Translated from Kibernetika i Sistemnyi Analiz, No. 3, May–June, 2020, pp. 17–29.
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Gubarev, V.F. Problem of Mathematical Data Interpretation. II. Distributed-Parameter Systems*. Cybern Syst Anal 56, 356–365 (2020). https://doi.org/10.1007/s10559-020-00252-7
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DOI: https://doi.org/10.1007/s10559-020-00252-7