On Adaptive Splines

Research outputpeer-review

Abstract

The paper discusses various methods of adaptive spline approximations for the flow of function values. The number of K knots in the adaptive grid determines the required amount of memory for storage of compression results. The number of M knots of the original grid characterizes the number of operations required to obtain adaptive compression. In the case of access to the derivative values the number of digital operations is proportional to the number M. If it does not have access to the last ones then the number of required operations has the order of M2 (in the general case). If additionally the approximated flow is convex, then the number of required operations has the order of M log2M. In all cases the result requires the computer memory amount of the order of K.

Original languageEnglish
Title of host publicationProceedings - 2nd International Conference on Mathematics and Computers in Science and Engineering, MACISE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages304-307
Number of pages4
ISBN (Electronic)9781728166957
DOIs
Publication statusPublished - Jan 2020
Event2nd International Conference on Mathematics and Computers in Science and Engineering, MACISE 2020 - Madrid
Duration: 18 Jan 202020 Jan 2020

Publication series

NameProceedings - 2nd International Conference on Mathematics and Computers in Science and Engineering, MACISE 2020

Conference

Conference2nd International Conference on Mathematics and Computers in Science and Engineering, MACISE 2020
CountrySpain
CityMadrid
Period18/01/2020/01/20

Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Engineering (miscellaneous)
  • Computational Mathematics
  • Control and Optimization
  • Modelling and Simulation
  • Computational Theory and Mathematics

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