How ill-conditioned must a matrix S be if it (block) diagonalizes a given matrix T, i.e. if S(-1)TS is block diagonal? The answer depends on how the diagonal blocks partition T's spectrum; the condition number of S is bounded below by a function of the norms of the projection matrices determined by the partitioning. In the case of two diagonal blocks we compute an S which attains this lower bound, and we describe almost best conditioned S's for dividing T into more blocks. We apply this result to bound the error in an algorithm to compute analytic functions of matrices, for instance exp(T). Our techniques also produce bounds for submatrices that appear in the square-root-free Choleskt and in the Gram-Schmidt orthogonalization algorithms.
Title
The Condition Number of Similarities that Diagonalize Matrices
Published
1983-07-05
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Other Identifiers
CSD-83-127
Type
Text
Extent
20 p
Archive
The Engineering Library
Usage Statement
Researchers may make free and open use of the UC Berkeley Library’s digitized public domain materials. However, some materials in our online collections may be protected by U.S. copyright law (Title 17, U.S.C.). Use or reproduction of materials protected by copyright beyond that allowed by fair use (Title 17, U.S.C. § 107) requires permission from the copyright owners. The use or reproduction of some materials may also be restricted by terms of University of California gift or purchase agreements, privacy and publicity rights, or trademark law. Responsibility for determining rights status and permissibility of any use or reproduction rests exclusively with the researcher. To learn more or make inquiries, please see our permissions policies (https://www.lib.berkeley.edu/about/permissions-policies).