Iterative rational Krylov algorithm (original) (raw)

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The iterative rational Krylov algorithm (IRKA), is an iterative algorithm, useful for model order reduction (MOR) of single-input single-output (SISO) linear time-invariant dynamical systems. At each iteration, IRKA does an Hermite type interpolation of the original system transfer function. Each interpolation requires solving shifted pairs of linear systems, each of size ; where is the original system order, and is the desired reduced model order (usually ).

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dbo:abstract The iterative rational Krylov algorithm (IRKA), is an iterative algorithm, useful for model order reduction (MOR) of single-input single-output (SISO) linear time-invariant dynamical systems. At each iteration, IRKA does an Hermite type interpolation of the original system transfer function. Each interpolation requires solving shifted pairs of linear systems, each of size ; where is the original system order, and is the desired reduced model order (usually ). The algorithm was first introduced by Gugercin, Antoulas and Beattie in 2008. It is based on a first order necessary optimality condition, initially investigated by Meier and Luenberger in 1967. The first convergence proof of IRKA was given by Flagg, Beattie and Gugercin in 2012, for a particular kind of systems. (en)
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rdfs:comment The iterative rational Krylov algorithm (IRKA), is an iterative algorithm, useful for model order reduction (MOR) of single-input single-output (SISO) linear time-invariant dynamical systems. At each iteration, IRKA does an Hermite type interpolation of the original system transfer function. Each interpolation requires solving shifted pairs of linear systems, each of size ; where is the original system order, and is the desired reduced model order (usually ). (en)
rdfs:label Iterative rational Krylov algorithm (en)
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