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

M.V. Gashnikov 1,2

1 Samara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia,
2 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.

Abstract:
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.

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

Citation:
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.

Acknowledgements:
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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