Low-Rank Cholesky Factor Krylov Subspace Methods for Generalized Projected Lyapunov Equations
Low-Rank Cholesky Factor Krylov Subspace Methods for Generalized Projected Lyapunov Equations
复制标题
广义投影 Lyapunov 方程的低阶 Cholesky 因子 Krylov 子空间方法
DOI:
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发表时间:
2017
期刊:
影响因子:
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通讯作者:
André K. Eppler
中科院分区:
文献类型:
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作者:
M. Bollhöfer;André K. Eppler
Large-scale descriptor systems arising from circuit simulation often require model reduction techniques. Among many methods, Balanced Truncation is a popular method for constructing a reduced order model. In the heart of Balanced Truncation methods, a sequence of projected generalized Lyapunov equations has to be solved. In this article we present a general framework for the numerical solution of projected generalized Lyapunov equations using preconditioned Krylov subspace methods based on iterates with a low-rank Cholesky factor representation. This approach can be viewed as alternative to the LRCF-ADI method, a well established method for solving Lyapunov equations. We will show that many well-known Krylov subspace methods such as (F)GMRES, QMR, BICGSTAB and CG can be easily modified to reveal the underlying low-rank structures.