构造保持对称结构的强线性化

H. Faßbender, J. Pérez, N. Shayanfar
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引用次数: 1

摘要

结构矩阵多项式的特征值问题在许多应用中都有出现。解决多项式特征值问题的标准方法是通过经典的Frobenius伴线性化,它可能不会保留矩阵多项式的结构。特别是,对称矩阵多项式的结构可能会丢失,而从计算的角度来看,构造保持对称结构的线性化是可取的。最近,在[5]中引入了新的块状克罗内克铅笔家族。应用块- kronecker铅笔,我们给出了对称矩阵多项式的保结构强线性化。当矩阵多项式具有奇次时,无论矩阵多项式是正则的还是奇异的,这些线性化都是强的。此外,在一些简单的非奇异条件下,构造了偶数次正则对称矩阵多项式的保结构强线性化。
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Constructing symmetric structure-preserving strong linearizations
Polynomials eigenvalue problems with structured matrix polynomials arise in many applications. The standard way to solve polynomial eigenvalue problems is through the classical Frobenius companion linearizations, which may not retain the structure of the matrix polynomial. Particularly, the structure of the symmetric matrix polynomials can be lost, while from the computational point of view, it is advisable to construct a linearization which preserves the symmetry structure. Recently, new families of block-Kronecker pencils have been introduced in [5]. Applying block-Kronecker pencils, we present structure-preserving strong linearizations for symmetric matrix polynomials. When the matrix polynomial has an odd degree, these linearizations are strong regardless of whether the matrix polynomial is regular or singular. Additionally, we construct structure-preserving strong linearizations for regular symmetric matrix polynomials of even degree under some simple nonsingularity conditions.
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