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Erschienen in: Pattern Recognition and Image Analysis 4/2019

01.10.2019 | MATHEMATICAL THEORY OF PATTERN RECOGNITION

Subjective Restoration of Mathematical Models for a Research Object, Its Measurements, and Measurement-Data Interpretation

verfasst von: Yu. P. Pyt’ev, O. V. Falomkina, S. A. Shishkin

Erschienen in: Pattern Recognition and Image Analysis | Ausgabe 4/2019

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Abstract

The problems of empirical reconstruction of the subjective model of a research object (RO), the subjective model of its measurements, their subjective analysis, and subjective interpretation of the measurement data are considered. To solve these problems, we use the mathematical formalism for subjective modeling (MFSM), subjective judgments made by the researcher–modeler (r.–m.) concerning the mathematical model of the RO and its measurements and based on his scientific experience and intuition. The subjective models of measurements of the RO and measurement-data interpretation are defined by the r.–m. as elements of a parametric family of smoothing splines. It is shown that the maximum posterior accuracy of the subjective interpretation of the measurement-experiment data, which is “observed” in the solution process for the problems of restoring the subjective models of the RO and its measurements, analysis, and measurement-data interpretation, can serve as a criterion for the truth of the subjective models of the measurement experiment and interpretation of the obtained measurement data, since the criterion for the accuracy of measurement-data interpretation is not used in the reconstruction of the above models. The paper suggests the principle of the maximum posterior accuracy of the subjective interpretation of measurement-experiment data as a criterion for the adequacy of subjectively reconstructed models of measurement experiments and interpretation of measurement data.

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Fußnoten
1
“Relatively” means that the numerical values of the measures Pl and Bel which differ from 0 and 1 cannot be meaningfully interpreted, and only their rank order is significant; see Subsection 2.1 of the present paper.
 
2
This condition guarantees the efficiency of subjective modeling and its unconditional applicability (see [2]).
 
3
The “coordinates” \(a,\hat {a} \in [0,1]\) in \(L,\hat {L}\) are given by the “coordinates” \(\gamma (a),\hat {\gamma }(\hat {a}) \in [0,1]\) in \(\gamma L,\hat {\gamma }\hat {L}\).
 
4
It was shown in the monograph [32] that problem (11) for \(n \geqslant q\) has the only solution for any \(y = {{y}_{1}}, \ldots ,{{y}_{n}}\).
 
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Metadaten
Titel
Subjective Restoration of Mathematical Models for a Research Object, Its Measurements, and Measurement-Data Interpretation
verfasst von
Yu. P. Pyt’ev
O. V. Falomkina
S. A. Shishkin
Publikationsdatum
01.10.2019
Verlag
Pleiades Publishing
Erschienen in
Pattern Recognition and Image Analysis / Ausgabe 4/2019
Print ISSN: 1054-6618
Elektronische ISSN: 1555-6212
DOI
https://doi.org/10.1134/S1054661819040138

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