ESTIMATING THE ERROR OF LOCAL INTERPOLATION SPLINE FUNCTIONS IN THE CLASS OF FUNCTIONS AND CREATING A DIGITAL PROCESSING MODEL OF GEOPHYSICAL SIGNALS.

In the modern scientific landscape, mathematical modeling plays a vital role in addressing challenges across various industrial domains. Among these, spline functions have emerged as effective tools, offering several advantages over classical interpolation methods [1,3,9]. This study focuses on error analysis and practical applications of a local interpolation cubic spline, constructed using a linear combination of parabolas with two shared points. Using experimentally acquired geophysical signal data, the error behavior of the spline model is examined through numerical analysis and graphical validation. The results confirm the model’s effectiveness in accurate signal reconstruction.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-10
DOI
https://doi.org/10.5281/zenodo.15634775
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
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article

ESTIMATING THE ERROR OF LOCAL INTERPOLATION SPLINE FUNCTIONS IN THE CLASS OF FUNCTIONS AND CREATING A DIGITAL PROCESSING MODEL OF GEOPHYSICAL SIGNALS.

Zenodo (CERN European Organization for Nuclear Research)
Seismic Imaging and Inversion Techniques
article

ESTIMATING THE ERROR OF LOCAL INTERPOLATION SPLINE FUNCTIONS IN THE CLASS OF FUNCTIONS AND CREATING A DIGITAL PROCESSING MODEL OF GEOPHYSICAL SIGNALS.

article en

Abstract

In the modern scientific landscape, mathematical modeling plays a vital role in addressing challenges across various industrial domains. Among these, spline functions have emerged as effective tools, offering several advantages over classical interpolation methods [1,3,9]. This study focuses on error analysis and practical applications of a local interpolation cubic spline, constructed using a linear combination of parabolas with two shared points. Using experimentally acquired geophysical signal data, the error behavior of the spline model is examined through numerical analysis and graphical validation. The results confirm the model’s effectiveness in accurate signal reconstruction.

Zenodo (CERN European Organization for Nuclear Research)
Tashkent University of Information Technology (UZ)
Openalex Percentile: Top 56%
Seismic Imaging and Inversion Techniques
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ESTIMATING THE ERROR OF LOCAL INTERPOLATION SPLINE FUNCTIONS IN THE CLASS OF FUNCTIONS AND CREATING A DIGITAL PROCESSING MODEL OF GEOPHYSICAL SIGNALS. · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS