Detail publikace

On Validity of Results of Approximate Symbolic Analysis

Originální název

On Validity of Results of Approximate Symbolic Analysis

Anglický název

On Validity of Results of Approximate Symbolic Analysis

Jazyk

en

Originální abstrakt

The paper studies the validity of results obtained using approximate symbolic analysis in the AC domain regarding the variation of network parameters. Traditional methods provide solutions based on nominal network parameters with no control over the approximation error when the parameters are varied. The method presented is based on the corner analysis that can be embedded in both the circuit and the formula simplification procedures. The properties of the method are demonstrated on an example analysis.

Anglický abstrakt

The paper studies the validity of results obtained using approximate symbolic analysis in the AC domain regarding the variation of network parameters. Traditional methods provide solutions based on nominal network parameters with no control over the approximation error when the parameters are varied. The method presented is based on the corner analysis that can be embedded in both the circuit and the formula simplification procedures. The properties of the method are demonstrated on an example analysis.

Dokumenty

BibTex


@inproceedings{BUT151075,
  author="Zdeněk {Kolka} and Viera {Biolková} and Dalibor {Biolek}",
  title="On Validity of Results of Approximate Symbolic Analysis",
  annote="The paper studies the validity of results obtained using approximate symbolic analysis in the AC domain regarding the variation of network parameters. Traditional methods provide solutions based on nominal network parameters with no control over the approximation error when the parameters are varied. The method presented is based on the corner analysis that can be embedded in both the circuit and the formula simplification procedures. The properties of the method are demonstrated on an example analysis.",
  address="IEEE",
  booktitle="2018 New Trends in Signal Processing (NTSP)",
  chapter="151075",
  doi="10.23919/NTSP.2018.8524081",
  howpublished="electronic, physical medium",
  institution="IEEE",
  number="1",
  year="2018",
  month="october",
  pages="90--93",
  publisher="IEEE",
  type="conference paper"
}