Publication detail

Algorithm for estimating error of symbolic simplification

KOLKA, Z. BIOLKOVÁ, V. DOBEŠ, J. HORÁK, M.

Original Title

Algorithm for estimating error of symbolic simplification

Type

conference paper

Language

English

Original Abstract

The paper deals with an improved algorithm for estimating errors during approximate symbolic analysis. A linear system can be solved symbolically. However, the size of the resulting formula grows exponentially with the matrix size. The approximate symbolic analysis omits insignificant terms of the exact formula to decrease its size, which, on the other hand, limits the validity of the approximate result. The proposed algorithm estimates, in a computationally feasible way, the approximation error over a region of system parameters. This makes it possible to maintain the validity of the results even if the tolerances of the system parameters are defined. The method is based on the first-order approximation of error functions. The algorithm is demonstrated using the SNAP symbolic analyzer, which has been developed by the authors.

Keywords

approximate symbolic analysis; CAD; electrical circuit

Authors

KOLKA, Z.; BIOLKOVÁ, V.; DOBEŠ, J.; HORÁK, M.

Released

22. 12. 2020

Publisher

E D P SCIENCES

Location

France

ISBN

9781713827269

Book

Proceedings of 2020 2nd International Conference on Computer Science

Pages from

1

Pages to

8

Pages count

8

URL

https://www.matec-conferences.org/articles/matecconf/pdf/2021/05/matecconf_cscns20_06023.pdf

BibTex

@inproceedings{BUT167660,
  author="Zdeněk {Kolka} and Viera {Biolková} and Josef {Dobeš} and Martin {Horák}",
  title="Algorithm for estimating error of symbolic simplification",
  booktitle="Proceedings of 2020 2nd International Conference on Computer Science",
  year="2020",
  volume="336",
  pages="1--8",
  publisher="E D P SCIENCES",
  address="France",
  doi="10.1051/matecconf/202133606023",
  isbn="9781713827269",
  url="https://www.matec-conferences.org/articles/matecconf/pdf/2021/05/matecconf_cscns20_06023.pdf"
}