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Title: Efficient numerical algorithms for balanced stochastic truncation

Creator:

Benner, Peter ; Quintana-Ortí, Enrique S. ; Quintana-Ortí, Gregorio

Date:

2001

Resource Type:

artykuł

Contributor:

Campbell, Stephen L. - ed.

Subtitle:

Numerical Analysis and Systems Theory

Group publication title:

AMCS, volume 11 (2001)

Abstract:

We propose an efficient numerical algorithm for relative error model reduction based on balanced stochastic truncation. The method uses full-rank factors of the Gramians to be balanced versus each other and exploits the fact that for large-scale systems these Gramians are often of low numerical rank. We use the easy-to-parallelize sign function method as the major computational tool in determining these full-rank factors and demonstrate the numerical performance of the suggested implementation of balanced stochastic truncation model reduction.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Resource Identifier:

oai:zbc.uz.zgora.pl:58806

Pages:

1123-1150

Source:

AMCS, volume 11, number 5 (2001) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

Subject and keywords:

model reduction stochastic realization balanced truncation sign function method Newton's method

Object collections:

Last modified:

Jul 14, 2025

In our library since:

Jul 22, 2021

Number of object content hits:

131

All available object's versions:

https://zbc.uz.zgora.pl/repozytorium/publication/65591

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Efficient numerical algorithms for balanced stochastic truncation Jul 14, 2025

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