Spectral radius is the greatest lower bound for some matrix norm

linear algebramatricesmatrix analysismatrix-normsspectral-radius

I'm studying matrix analysis with Horn and Johnson's book.

I have something trouble while reading the book.

There is lemma 5.6.10 lemma and the following is the proof of that Proof of lemma.

I have trouble in two lines below from the matrix such that
1-norm of $D_t \triangle D_t^{-1}$ is less and equal to $\rho(A)+\epsilon$.

1-norm is defined as the sum of all element in the matrix.

I understood that off-diagonal elements can be bounded by epsilon for large $t$. However, I cannot understand how does the sum of absolute values of eigenvalues will be bounded by spectral radius of $A$.

Best Answer

The $1$-norm of a matrix is usually the max column sum (that is, the max column $\ell_1$-norm). Are you sure that your book defines it as you said?

If it is the max column sum, then the norm will be $|\lambda_j|$ plus off-diagonal elements. The off-diagonal elements are bounded by $\epsilon,$ and the spectral radius will bounded any $|\lambda_j|$, by definition.

Related Question