Hyman’s method revisited
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摘要
The QR algorithm is considered one of the most reliable methods for computing matrix eigenpairs. However, it is unable to detect multiple eigenvalues and Jordan blocks. Matlab’s eigensolver returns heavily perturbed eigenvalues and eigenvectors in such cases and there is no hint for possible principal vectors. This paper calls attention to Hyman’s method as it is applicable for computing principal vectors and higher derivatives of the characteristic polynomial that may help to estimate multiplicity, an important information for more reliable computation. We suggest a test matrix collection for Jordan blocks. The first numerical tests with these matrices reveal that the computational problems are deeper than expected at the beginning of this work.
论文关键词:15A18,15A21,65F15,QR method,Multiple eigenvalues,Hessenberg matrices,Jordan canonical form,Newton method,Hyman’s method
论文评审过程:Available online 7 August 2008.
论文官网地址:https://doi.org/10.1016/j.cam.2008.08.004