Search Results
Search type | Search syntax |
---|---|
Tags | [tag] |
Exact | "words here" |
Author |
user:1234 user:me (yours) |
Score |
score:3 (3+) score:0 (none) |
Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
Views | views:250 |
Code | code:"if (foo != bar)" |
Sections |
title:apples body:"apples oranges" |
URL | url:"*.example.com" |
Saves | in:saves |
Status |
closed:yes duplicate:no migrated:no wiki:no |
Types |
is:question is:answer |
Exclude |
-[tag] -apples |
For more details on advanced search visit our help page |
The study of the properties of real and complex matrices that are more close to analysis and operator theory. For instance: the properties of positive definite matrices, matrix inequalities, perturbation analysis, matrix functions, inequalities between eigenvectors and singular values, majorization.
1
vote
positive semidefiniteness: a psd matrix substracted by another rank 1 psd matrix
This is easy to formulate as a semidefinite programming problem.
First, let $X=xx^{T}$. The semidefiniteness constraint becomes
$A-\lambda X \succeq 0$
Next, use a standard technique to handle t …
7
votes
Accepted
Explicit formula for Cholesky factorization in a special case
The matrix $\alpha J$ is a rank one matrix, so there are simple update/downdate formulas for computing the Choleksy factorization of $Q+sI-\alpha J$ if you start with the factorization of $Q+sI$.
I …
1
vote
Norm bound on eigen-vector change caused by rank-one update
A tiny change can result in a shift of the dominant eigenvalue's eigenspace to something that is completely orthogonal to the dominant eigenvalue's eigenspace of $A$.
For example, let
$A=I-\epsil …