Publication detail

Exploiting Matrix Sparsity for Symbolic Analysis

KOLKA, Z., BIOLKOVÁ, V., BIOLEK, D.

Original Title

Exploiting Matrix Sparsity for Symbolic Analysis

English Title

Exploiting Matrix Sparsity for Symbolic Analysis

Type

journal article - other

Language

en

Original Abstract

This paper deals with a method for symbolic approximation that exploits the sparsity of circuit matrix to achieve an acceptable speed for large circuits. The method is based on a simplification of the equations of circuit models of linear or linearized circuits in the frequency domain. The simplified model is then analyzed symbolically. The algorithm proposed has been developed with the aim of obtaining maximum computational efficiency.

English abstract

This paper deals with a method for symbolic approximation that exploits the sparsity of circuit matrix to achieve an acceptable speed for large circuits. The method is based on a simplification of the equations of circuit models of linear or linearized circuits in the frequency domain. The simplified model is then analyzed symbolically. The algorithm proposed has been developed with the aim of obtaining maximum computational efficiency.

Keywords

symbolic analysis, sparse matrices

RIV year

2004

Released

10.12.2004

Pages from

2278

Pages to

2281

Pages count

4

BibTex


@article{BUT45902,
  author="Zdeněk {Kolka} and Viera {Biolková} and Dalibor {Biolek}",
  title="Exploiting Matrix Sparsity for Symbolic Analysis",
  annote="This paper deals with a method for symbolic approximation that exploits the sparsity of circuit matrix to achieve an acceptable speed for large circuits. The method is based on a simplification of the equations of circuit models of linear or linearized circuits in the frequency domain. The simplified model is then analyzed symbolically. The algorithm proposed has been developed with the aim of obtaining maximum computational efficiency.",
  chapter="45902",
  journal="WSEAS Transactions on Circuits",
  number="10",
  volume="3",
  year="2004",
  month="december",
  pages="2278",
  type="journal article - other"
}