2
votes
1answer
131 views
Coercive Symmetric Bilinear form on a Hilbert space
I need to show one of the two following equivalent results. If true, it must be a simple proof but I do not seem to be able to make it work. Thank you in advance.
1) Consider a co …
-1
votes
1answer
156 views
Coercive Symmetric Bilinear form on a Hilbert space
I need to show the two following results. If true, it must be a simple proof but I do not seem to be able to make it work. Thank you in advance.
Consider a continuous symmetric bi …
2
votes
0answers
70 views
Relation between the eigenspace of a covariance matrix and eigenspace of correlation matrix
I was discussing applying Principal Component Analysis to a covariance matrix versus applying PCA to the corresponding correlation matrix with a collegue. This led me to think abou …
0
votes
0answers
31 views
is there any fast algorithm for tree graph eigendecomposition?
Is there any fast algorithm that can performs the eigendecomposition of the Laplacian matrix of a tree graph?
Thank you!
1
vote
0answers
50 views
Eigenvectors of contraction times projection
Suppose $A$ is a real $n\times n$ matrix with real eigenvalues:
$$
1=\lambda_1>|\lambda_2|\ge \ldots\ge |\lambda_n|>0.
$$
Suppose $B$ is an involution, for simplicity let us assum …
4
votes
1answer
123 views
Sum of commuting semisimple operators
Let $V$ be a finite dimensional vector space over a field $K$. An operator $T:V\to V$ is called semi-simple if every $T$-invariant subspace of $V$ has a complement(for algebraicall …
2
votes
2answers
437 views
Singular Value Decomposition of Noisy Matrices
I am an engineer who makes measurements of a variable over a grid
of, say, $m\times n$. Since these are actual measurements, the true
values are always corrupted by noise, and what …
3
votes
2answers
289 views
Eigenvalues of a Symmetric Positive Semi-Definite (PSD) matrix after rank one update
I have a Symmetric Positive Semi-Definite matrix $A$ which i know its eigenvalue and eigenvectors. let $v$ and $u$ be a random column vector. i want to know if it is possible to ha …
2
votes
3answers
438 views
Eigenvectors and eigenvalues of nonsymmetric Tridiagonal matrix
Hi, the question is following: We have one matrix
$$\begin{pmatrix}
-\beta & \Delta & 0 & 0 &\cdots & 0 & 0 & 0 \newline
\beta & -(\beta+\Delta) …
0
votes
0answers
158 views
Comparing eigenvalues of two matrices [closed]
Suppose we have
$A=\left(\begin{array}{cccc}
1 & 1 & 1 & 0\\
1 & 3 & 0 & 0\\
1 & 0 & 2 & 1\\
0 & 0 & 1 & 3
\end{array}\right)$
and …
3
votes
1answer
196 views
Eigenvectors of asymmetric graphs
Let $G$ be an asymmetric connected graph. Then is it always the case that at least one of the eigenvectors of its adjacency matrix $A$ consists entirely of distinct entries?
Thank …
8
votes
4answers
2k views
Eigenvectors and eigenvalues of Tridiagonal matrix
Hi, is it possible to analytically evaluate the eigenvectors and the eigenvalues of a tridiagonal matrix of the form :
$$
\mathcal{T}^{a}_n(p,q) = \begin{pmatrix}
0 & q &a …
4
votes
2answers
408 views
Perturbation theory for the generalized eigenvalue problem
Is there a standard reference for the perturbation theory of the generalized eigenvalue problem?
More specifically, I would like to get a systematic expansion for the problem
…
2
votes
0answers
190 views
Common eigenvector
I have little experience with functional analysis beyond an undergraduate basic course, and I'm dealing with the following problem:
let $V$ be an infinite-dimensional locally conv …
0
votes
1answer
4k views
Difference between Principal Component Analysis(PCA) and Singular Value Decomposition(SVD)?
I am confused between PCA and SVD.
The wikipedia page for PCA has this line. "PCA can be done by eigenvalue decomposition of a data covariance matrix or singular value decompositi …

