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Jacobi-Davidson type methods for generalized eigenproblems and polynomial eigenproblems : part I

机译:用于广义自问题和多项式自问题的Jacobi-Davidson型方法:第一部分

摘要

In this paper we will show how the Jacobi-Davidson iterative method can be used to solve generalized eigenproblems. Similar ideas as for the standard eigenproblem are used, but the projections, that are required to reduce the given problem to a small manageable size, need more attention. We show that by proper choices for the projection operators quadratic convergence can be achieved. The advantage of our approach is that none of the involved operators needs to be inverted. It turns out that similar projections can be used for the iterative approximation of selected eigenvalues and eigenvectors of polynomial eigenvalue equations. This approach has already been used with great success for the solution of quadratic eigenproblems associated with acoustic problems.
机译:在本文中,我们将展示如何使用Jacobi-Davidson迭代方法来解决广义特征问题。使用了与标准本征问题类似的想法,但是将给定问题减少到较小的可管理规模所需的预测需要引起更多关注。我们表明,通过对投影算子的正确选择,可以实现二次收敛。我们的方法的优势在于,不需要涉及任何运算符。事实证明,相似的投影可用于多项式特征值方程的选定特征值和特征向量的迭代逼近。这种方法已经成功地用于解决与声学问题有关的二次特征问题。

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