Utkir Khamdamov  1 , Alisher Abdullayev2 , Mukhriddin Mukhiddinov1 , and Sirojiddin Xalilov3

1Department of Hardware and Software of Control Systems in Telecommunications, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent 100200, Uzbekistan
2Department for Development of Information and Communication Technologies, Ministry of Higher and Secondary Specialized Education of the Republic of Uzbekistan, Tashkent, 100095, Uzbekistan
3Department of Information Technologies, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent 100200, Uzbekistan


Received: July 27, 2020
Accepted: September 29, 2020
Publication Date: April 1, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202104_24(2).0003  


With the development of the digital signal processing systems, the tasks of discrete signal reconstruction have become most actual, which can be related to the function of interpolation tasks in computational mathematics. This paper presents the results of using local basis splines as a mathematical apparatus for approximation one-dimensional and two-dimensional signals used in the field of geophysics information systems. The internet service now being built would enable the geophysical information system to be accessed by organizations and people associated with the universities and scientific institutes. As a result of research, the effective methods and algorithms for calculating approximation coefficients based on windows consisting of certain numbers of signal samples are proposed. All experiments were carried out for approximation values of the linear and harmonic form analytical functions, as well as to restore the geophysical signals forms. To evaluate the reliability of the proposed methods and algorithms, the approximation results were estimated by calculating the mean square error of signal recovery

Keywords: spline, basic spline, cubic spline, interpolation, approximation, information systems, information and communication technologies, signal recovery, geophysical signal, geophysics, gravity exploration


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