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Highly Cited

2010

Highly Cited

2010

Krylov subspace methods (KSMs) are iterative algorithms for solving large, sparse linear systems and eigenvalue problems. Current… Expand

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Highly Cited

2010

Highly Cited

2010

The numerical solution of linear systems with certain tensor product structures is considered. Such structures arise, for example… Expand

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Highly Cited

2006

Highly Cited

2006

Many problems in science and engineering require the solution of a long sequence of slowly changing linear systems. We propose… Expand

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Highly Cited

2005

Highly Cited

2005

This paper describes the use of Krylov subspace methods in the model reduction of power systems. Additionally, a connection… Expand

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Highly Cited

2002

Highly Cited

2002

In this paper we analyze the null-space projection (constraint) indefinite preconditioner applied to the solution of large-scale… Expand

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Highly Cited

1997

Highly Cited

1997

This dissertation focuses on e ciently forming reduced-order models for large, linear dynamic systems. Projections onto unions of… Expand

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Highly Cited

1995

Highly Cited

1995

Approximations to the solution of a large sparse symmetric system of equations are considered. The conjugate gradient and minimum… Expand

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Highly Cited

1992

Highly Cited

1992

In this note a theoretical analysis of some Krylov subspace approximations to the matrix exponential operation $\exp (A)v$ is… Expand

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Highly Cited

1990

Highly Cited

1990

Several implementations of Newton-like iteration schemes based on Krylov subspace projection methods for solving nonlinear… Expand

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Highly Cited

1981

Highly Cited

1981

Some algorithms based upon a projection process onto the Krylov subspace K/sub m/ = Span(r/sub 0/, Ar/sub 0/,..., A/sup m-1/r/sub… Expand

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