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Adaptive interpolation based on optimization of the decision rule in a multidimensional feature space

M.V. Gashnikov 1,2

Samara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia,
IPSI RAS – Branch of the FSRC "Crystallography and Photonics" RAS,
Molodogvardeyskaya 151, 443001, Samara, Russia

 PDF, 779 kB

DOI: 10.18287/2412-6179-CO-661

Pages: 101-108.

Full text of article: Russian language.

An adaptive multidimensional signal interpolator is proposed, which selects an interpolating function at each signal point by means of the decision rule optimized in a multidimensional feature space using a decision tree. The search for the dividing boundary when splitting the decision tree vertices is carried out by a recurrence procedure that allows, in addition to the search for the boundary, selecting the best pair of interpolating functions from a predetermined set of functions of an arbitrary form. Results of computational experiments in nature multidimensional signals are presented, confirming the effectiveness of the adaptive interpolator.

multidimensional signal, adaptive interpolation, multidimensional feature, optimization, interpolation error.

Gashnikov MV. Adaptive interpolation based on optimization of the decision rule in a multidimensional feature space. Computer Optics 2020; 44(1): 101-108. DOI: 10.18287/2412-6179-CO-661.

The work was funded by the Russian Foundation for Basic Research under RFBR grant 18-01-00667 and the RF Ministry of Science and Higher Education within the state project of FSRC “Crystallography and Photonics” RAS under agreement 007-GZ/Ch3363/26.


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