All Questions
Tagged with linear-algebra na.numerical-analysis
176 questions
4
votes
0
answers
382
views
Pseudoinverse of column submatrix, from pseudoinverse of entire matrix.
Hello,
I am working on a numerical method for the least-squares solution of a linear system. I know that I can approximate the solution to $Ax=b$ with $x=A^+b$, where $A^+$ is the Moore-Penrose ...
- 41
2
votes
2
answers
402
views
Maximization of a matrix product by iterative methods
This might not be very difficult, but I think I may have gotten a little confused.
Suppose we are given a matrix A, and would like to find the vector x of modulus 1 which maximises the product xt A x ...
- 60.6k
5
votes
4
answers
2k
views
Determining a recurrence relation
I would like to solve the general problem of determining a linear recurrence relation that fits a given integer sequence of length $n$, or stating that none exists (with fewer than $n/2-k$ ...
- 39.9k
2
votes
0
answers
187
views
Recovering a linear map from a non-linear approximation
The problem described here is algorithmic. We are given "black box access" to a map $f:R^d\to R^d$. By this we mean that one may query the value of $f(v)$ for an arbitrary $v\in R^d$.
We assume that ...
1
vote
2
answers
262
views
How to approx. decompose a sym. p.d. matrix M into X'X?
M: pxp symmetric p.d. matrix with unit diagonals
n: number much smaller than p
Want a nonrandom nxp matrix X such that X'X is
close to M element-wise. If n gets larger, hopefully
difference ...
- 17.9k
4
votes
1
answer
1k
views
An optimization problem in numerical linear algebra
Provided two diagonal real matrix which has positive entries, $V$ and $U$.
Find a real matrix $A$, satisfying $A^TA=a^2I$ for some scalar $a$, to minimise
$\left|A^TVA-U\right|\quad\quad(*)$ ...
- 52.3k
3
votes
1
answer
346
views
enlarge the separation between two matrices
The separation between two square matrices $A$ and $B$, often used as a measure of the sensitivity of invariant subspace problems, is defined as
$$
\operatorname{sep}(A,B)=\min_{X\neq 0}\frac{\left\...
- 28.6k
2
votes
3
answers
285
views
is there any efficient way to compute the follow matrix equations easily
Let $A$ and $D$ are $n\times n$ diagnal matrices, and $B$ is an $n\times n$ orthogonal matrix. Is there any efficient way to compute the follow matrix equations easily?
$\sum_{i=0}^{k} A^i \cdot B^T \...
- 391
3
votes
0
answers
682
views
How to bound the second largest eigenvalue of a transition matrix of a non-irreducible Markov chain?
I have found several bounds (e.g., Cheeger, Poincare) for the case that the Markov chain is irreducible and reversible, however my Markov chain has one absorbing state. Any bound would be helpful, but ...
- 31
0
votes
1
answer
2k
views
Solving 5 eqns with 6 unknowns in a 2x3 contingency matrix, is there a unique solution? [closed]
Background
I have the following equations:
$$a+b+c=6$$
$$d+e+f=15$$
$$a+d=5$$
$$b+e=7$$
$$c+f=9$$
This is a 2x3 matrix $[a b c, d e f]$ where the marginal totals are fixed. In addition, all of the ...
CommunityBot
- 1
2
votes
1
answer
3k
views
Is it possible to decompose a symmetric, positive definite matrix in this way?
Let $\Sigma$ be a symmetric positive definite matrix. Then the Cholesky decomposition gives us $\Sigma=LL'$ where $L$ is lower triangular and unique.
Under what conditions (if any) does there exist ...
- 96.4k
9
votes
1
answer
385
views
Adding a multiple of the Identity to a LU factorized matrix
Suppose a square, dense, symmetric matrix $A$ has been factorized into $L$ and $U$ components by performing a LU decomposition. Now let $B = A+\lambda I$. Is there any way to efficiently compute the ...
CommunityBot
- 1
4
votes
3
answers
3k
views
Making MATLAB svd robust to transpose operation
I'm playing with MATLAB's svd function to compute the svd of
[ 1 4 7 10
2 5 8 11
3 6 9 12 ]
When I type [U1, ~, ~] = svd(...
- 86
1
vote
2
answers
6k
views
Square root of non-positive definite matrix
Finding square root of matrices using Cholesky decomposition is limited to positive definite matrices. Any other method to find square root of matrix which has some diagonal values approximately zero (...
6
votes
4
answers
7k
views
Why do we want to have orthogonal bases in decompositions?
In the decompositions I encountered so far, we all had orthogonal set of bases. For example in Singular Value Decomposition, we had orthogonal singular right and left vectors, in [discrete] cosine ...
- 12.7k
4
votes
0
answers
453
views
Convergence of the relaxation method for every parameter in the relevant disk
For large size matrices, the resolution of linear systems $Ax=b$ is often done iteratively. The matrix $A$ is split as $A=M-N$, with $M$ invertible, and one performs
$$x^{k+1}=M^{-1}(Nx^k+b).$$
The ...
- 52.3k
1
vote
1
answer
383
views
Relaxation Scheme for $Au=f$ error analysis
Hello
I'm trying to answer this question, but am completely stuck.
Argue that in analyzing the error in a stationery linear relaxation scheme applied to $Au=f$, it is sufficient to consider $Au=0$ ...
- 52.3k
2
votes
0
answers
241
views
subspace separation and M-matrices
The separation between two square matrices $A$ and $B$, often used as a measure of the sensitivity of invariant subspace problems, is defined as
$$
\operatorname{sep}(A,B)=\min_{X\neq 0}\frac{\left\...
- 20.2k
8
votes
5
answers
15k
views
Eigenvalues of A+B where A is symmetric positive definite and B is diagonal
If I have a symmetric positive definite matrix A and a diagonal matrix B, and I know the eigenvalues of both A and B (by iterative numerical computation in A's case and trivially for B), is there any ...
CommunityBot
- 1
3
votes
2
answers
3k
views
distributed incremental SVD
Hello all,
I need some theoretical pointers (formulas, articles, online links) on how to merge Singular Value Decompositions (SVD) of two matrices (two different sets of observations over the same ...
- 153
4
votes
1
answer
548
views
O(n^2) algorithm to approximate the sum of the log of the singular values of a matrix
Given an $M \times N$ matrix of rank $N$ ($M \ge N$) with $i^{th}$ singular value $\sigma_i$, does their exist an $O(M^2)$ algorithm for approximating the sum $ H =\sum_{i=1}^N \log(\sigma_i)$ with ...
- 114k
1
vote
0
answers
1k
views
Covariance matrix formula interpretation - what am I missing?
I'm reading a paper that outlines the calculation of a covariance matrix like the following:
$C=\displaystyle\sum^{N_b}_{i=1}\vec{x}_i\vec{x}_i^T$
What is the order of this matrix? My interpretation ...
- 111
1
vote
2
answers
540
views
Using Wavelet Transforms to Approximate Matrices
It's a long time since I worked on this kind of problem, so please bear with me.
I have an approximate inverse matrix that I'm using as a preconditioner to solve the conjugate gradient method. ...
- 169
0
votes
2
answers
4k
views
Convergence of iterative algorithm.
For quite a long time I'm trying to prove convergence of an iterative algorithm in case of a particular system of nonlinear equations.
Here are some characteristics of this system:
It consists of n ...
CommunityBot
- 1
1
vote
0
answers
393
views
iterated characteristic polynomials
If I have $N$ $M\times M$ symmetric positive definite matrices $A_i$ and an $N\times N$ positive semi-definite symmetric matrix B, let the $N\times N$ matrix $C_{ij}(\lambda)=B_{ij}$ for $i\ne j$ and $...
- 15.4k
5
votes
1
answer
2k
views
Inverting a covariance matrix numerically stable
Given an $n\times n$ covariance matrix $C$ where $n$ around $250$, I need to calculate $x\cdot C^{-1}\cdot x^t$ for many vectors $x \in \mathbb{R}^n$ (the problem comes from approximating noise by an $...
- 51