Further lower bounds for the smallest singular value
β Scribed by Charles R. Johnson; Tomasz Szulc
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 464 KB
- Volume
- 272
- Category
- Article
- ISSN
- 0024-3795
No coin nor oath required. For personal study only.
β¦ Synopsis
In an earlier paper of the first author, Gersgorin's theorem was used in a novel way to give a simple lower bound for the smallest singular value of a general complex matrix. That lower bound was stronger than previous published bounds. Here, we use three variants of Gersgorin's theorem in a similar way to give further lower bounds.
Each of the new bounds is more complicated, but generally stronger, than the pure Gersgorin-based bound. The three new bounds are mutually noncomparable.
π SIMILAR VOLUMES
We derive monotonic sequences of bounds for the extreme singular values. In particular, we find further lower bounds for the smallest singular value which improve the bounds of Yu and Gun. Also, we give new upper bounds for the spectral condition number. ~
In the first part, we obtain two easily calculable lower bounds for A -1 , where β’ is an arbitrary matrix norm, in the case when A is an M-matrix, using first row sums and then column sums. Using those results, we obtain the characterization of M-matrices whose inverses are stochastic matrices. With