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**Krylov-subspace methods for reduced-order modeling in circuit simulation.**
*(English)*
Zbl 0964.65082

Author’s summary: The simulation of electronic circuit involves the numerical solution of very large-scale, sparse, in general nonlinear, systems of differential-algebraic equations. Often, the size of these systems can be reduced considerably by replacing the equations corresponding to linear subcircuits by approximate models of much smaller state-space dimension. We describe the use of Krylov-subspace methods for generating such reduced-order models of linear subcircuits. Particular emphasis is on reduced-order modeling techniques that preserve the passivity of linear RLC subcircuits.

Reviewer: Peter Reichensperger (Oberasbach)

### MSC:

65L80 | Numerical methods for differential-algebraic equations |

65F10 | Iterative numerical methods for linear systems |

34A09 | Implicit ordinary differential equations, differential-algebraic equations |

94C05 | Analytic circuit theory |

### Keywords:

Lanczos algorithm; Arnoldi process; Pad/’e approximation; simulation of electronic circuit; systems of differential-algebraic equations; Krylov-subspace methods; reduced-order modeling
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\textit{R. W. Freund}, J. Comput. Appl. Math. 123, No. 1--2, 395--421 (2000; Zbl 0964.65082)

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### References:

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