Questions tagged [numerical-linear-algebra]
{numerical-linear-algebra} questions involving algorithms for linear algebra computations.
296
questions
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1
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Is it possible to solve this kind of quadratic simultaneous equations?
$$\mathbf{x} = (x_1, x_2, ..., x_N)^T \in \mathbb{R}^{N} \\
\mathbf{A}_i \in \mathbb{R}^{N \times N},
\mathbf{b}_i \in \mathbb{R}^N ,
\mathbf{c}_i \in \mathbb{R}\\
\mathbf{x}^T\mathbf{A}_i\mathbf{x}...
- 11
2
votes
1
answer
245
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Usage and origin of the terms dictionary and atom in compressed sensing
In compressed sensing two terms or perhaps fancy word are frequently encountered. One is the dictionary and the other is atom. The dictionary is the matrix and its columns are called "atoms" ...
- 790
17
votes
0
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260
views
Why does the random shift in the QR eigenvalue algorithm work in the non-symmetric case over the complex field
I tried to implement the QR algorithm for non-symmetric matrices with complex entries to show to my students. The main part of the implementation was standard: the Householder reduction to the ...
- 60.9k
2
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66
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Characteristics of conjugate gradients' iterations for a matrix with clustered spectrum
I am interested in solving
\begin{equation}
Ax = b
\end{equation}
for a large sparse linear symmetric positive definite matrix $A$ by Conjugate Gradients method. (These systems usually come as ...
- 121
4
votes
1
answer
282
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rank of an integer valued matrix
I make some numerical experiments, involving rank of integer valued matrices of the size about $14\times 24$. As the matrix is integer valued, theoretically there should be no room for errors. However ...
- 738
1
vote
1
answer
147
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Nearest Kronecker product to sum of Kronecker products
I am interested in efficiently finding the closest Kronecker decomposition to the sum of $k$ Kronecker products:
$$\min_{A,B} || A \otimes B - \sum_{i=1}^k A_i \otimes B_i ||_F$$
where $A,A_i$ are $p \...
- 111
1
vote
0
answers
92
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Vandermonde-type factorization of moment matrix?
Consider $n,d \in \mathbb{N}_{>0}$, there are many functions $y:\mathbb{N}^{n} \to \mathbb{R}$. Now for simplicity, we denote $y(\alpha)$ to be $y_{\alpha}$. Let $|\alpha| = \sum_{i=1}^{n}\alpha_{i}...
- 245
1
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0
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65
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Reference request: finding entries that prevent matrix from being correlation matrix
I am currently doing some research with a quantitative finance firm and my supervisor has raised an interesting question that shows up a lot with their clients: quite often, clients will want to do ...
- 741
0
votes
0
answers
53
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Concentration of bilinear forms
This is a bit vague so I'll begin by indicating the motivation. I am looking for ways to [do something interesting or useful] with the self-attention in transformer models. Ultimately the self-...
- 6,922
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69
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Computing smallest singular value of a matrix with explicit error control?
Many good algorithms are out there computing truncated SVD: What is the time complexity of truncated SVD?.
I am trying to implement some codes to find the smallest singular value of a big matrix $A$. ...
- 1,683
0
votes
1
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79
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Matrix quantization and effect on singular values
Let $A$ and $B$ be an $N\times n$ matrix with $n\le N$, and let $\sigma_1(X),\dots \sigma_n(X)$ denote the singular values of $X\in \{A,B\}$. Do we have upper and lower bounds for
$$
\|
\sigma_i(A)-\...
- 5,079
0
votes
0
answers
27
views
The selection of minimal generating sets in Lie algebra
Suppose $A$ is a Lie algebra on field $F_{p}$ with $[A,A,A]=0$. Denote $\{a_{1},\cdots,a_{d}\}$ is a minimal generating set of $A$.It's possible that $[a_{i},a_{j}]=0$ for some $1\leq i<j\leq d$ ...
- 161
7
votes
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228
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Efficiently solve the Sylvester equation $AX+XA = C$ where $X$ is skew-symmetric
Is there a way (more efficient than the standard vectorization) to solve the following Sylvester equation in the skew-symmetric matrix $X$ $$AX+XA = C$$ where the matrix $A$ is symmetric positive ...
- 173
1
vote
0
answers
177
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Connection of eigenspace of finite Hilbert matrix and its continuous operator counterpart
I am trying to understand the connection between the eigenspace of the continuous operator
$$
H(x,y) = \frac{1}{x+y}
$$
which is nothing but the square of the Laplace operator, and its discrete ...
- 33
2
votes
1
answer
112
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Cosine-sine decomposition yields zero diagonals
I have implemented the Cosine-Sine decomposition of a square matrix in Mathematica. That is, for a given matrix $U$ (where in my use-case, $U$ is unitary) with equally-sized partitions
$$
U = \begin{...
- 173