Given a diagonalizable matrix $A$, we study the stability of its invariant subspaces when its matrix of eigenvectors is ill-conditioned. Let $\mathcal{X}_1$ be some invariant subspace of $A$ and $X_1$ be the matrix storing the right eigenvectors that spanned $\mathcal{X}_1$. It is generally believed that when the condition number $\kappa_2(X_1)$ gets large, the corresponding invariant subspace $\mathcal{X}_1$ will become unstable to perturbation. This paper proves that this is not always the case. Specifically, we show that the growth of $\kappa_2(X_1)$ alone is not enough to destroy the stability. As a direct application, our result ensures that when $A$ gets closer to a Jordan form, one may still estimate its invariant subspaces from the noisy data stably.
翻译:根据一个可变化矩阵$A$,当其变异子空间的矩阵条件不当时,我们研究其变异子空间的稳定性。当其变异子空间的基质条件变大时,当其变异子空间的基质条件变大时,我们研究其变异子空间的稳定性。当其变异子空间的基质变异的基质变异时,当其变异子空间的基质变异的基质变异时,当其变异子空间的基质变异的基质变异时,当其变异亚空间的基质变异的基质变异时,当其变异子空间的基质变异时,当其变异性子空间的基质变异性变异时,当其变异异性子空间的基质变异,当其变异性子空间的基质变异数据变异时,人们仍可以估计其变异的基质亚空间的基质空间将变得不稳定。具体地证明,仅是,仅增长的亚值还不足以破坏稳定性。作为直接应用的结果,当美元接近约旦时,当年的A美元接近约旦时,人们对热数据进行估算。