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Efficient Numerical Algorithms for Balanced Stochastic Truncation
International Journal of Applied Mathematics and Computer Science, Tome 11 (2001) no. 5, pp. 1123-1150 Cet article a éte moissonné depuis la source Library of Science

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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.
Keywords: model reduction, stochastic realization, balanced truncation, sign function method, Newton's method
Mots-clés : algorytmy, metoda Newtona 
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     title = {Efficient {Numerical} {Algorithms} for {Balanced} {Stochastic} {Truncation}},
     journal = {International Journal of Applied Mathematics and Computer Science},
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     language = {en},
     url = {http://geodesic.mathdoc.fr/item/IJAMCS_2001_11_5_a5/}
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Benner, P.; Quintana-Orti, E. S.; Quintana-Orti, G. Efficient Numerical Algorithms for Balanced Stochastic Truncation. International Journal of Applied Mathematics and Computer Science, Tome 11 (2001) no. 5, pp. 1123-1150. http://geodesic.mathdoc.fr/item/IJAMCS_2001_11_5_a5/