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3 votes
1 answer
143 views

A problem about matrix inverse and regularization methods

I'm researching the problem of solving the equation $A\mathbf{x}=\mathbf{b}$ with ill-conditioned matrices. We know that if we solve it directly, like $\mathbf{x}=\mathrm{inv}(A)\ast\mathbf{b}$, then ...
1 vote
1 answer
294 views

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 \...
1 vote
0 answers
95 views

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}...
7 votes
1 answer
305 views

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 ...
34 votes
3 answers
3k views

Quickly determining if a matrix has any PSD completion

Given $m$ entries of an $n \times n$ matrix, is it possible to determine in $O(m n)$ time whether there is any positive semidefinite completion? Slightly more precisely: for simplicity let's assume ...
21 votes
2 answers
18k views

Complexity of linear solvers vs matrix inversion

Solving linear equations can be reduced to a matrix-inversion problem, implying that the time complexity of the former problem is not greater than the time complexity of the latter. Conversely, given ...
11 votes
3 answers
9k views

Eigenvectors of a symmetric positive definite Toeplitz matrix

I wish to efficiently compute the eigenvectors of an n x n symmetric positive definite Toeplitz matrix K. A full eigendecomposition would be even better. Although I assumed this would be a well ...
1 vote
0 answers
179 views

QR algorithm for eigenvalues and eigenvectors of large symmetric matrices

I am trying to write a QR algorithm in Python for eigenvectors and eigenvalues finding for large symmetric matrices, My initial thought was to use Householder transformation with a Wilkinson shift ...
38 votes
10 answers
18k views

Fast matrix multiplication

Suppose we have two $n$ by $n$ matrices over particular ring. We want to multiply them as fast as possible. According to wikipedia there is an algorithm of Coppersmith and Winograd that can do it in $...
7 votes
2 answers
244 views

Finding $\theta$ such that at least one eigenvalue of $A(\theta)$ is real

Is there a known method to find a set of $\theta$ such that at least one eigenvalue of $A(\theta)$ is purely real? Assume $A(\theta)$ is a real square matrix whose elements are linear functions of a ...
34 votes
3 answers
6k views

Why is uncomputability of the spectral decomposition not a problem?

Below, we compute with exact real numbers using a realistic / conservative model of computability like Type Two Effectivity. Assume that there is an algorithm that, given a symmetric real matrix $M$, ...
0 votes
0 answers
232 views

How to analyse the range of eigenvalues of a symmetric and indefinite matrix?

Let $G$ be a symmetric and indefinite matrix defined as follows $$ G := S - \begin{pmatrix} I_n & I_n \\ I_n & I_n \end{pmatrix},$$ where $S$ is a symmetric positive definite matrix of size $...
15 votes
2 answers
7k views

Efficient rank-two updates of an eigenvalue decomposition (or more generally SVD)

Let $A$ be a symmetric matrix with eigenvalue decomposition $UDU^T$. Golub, et al.1 and Bunch, et al.2 have shown that given such an $A$, the eigenvalue decomposition of $A+\rho xx^t$ may be computed ...
1 vote
2 answers
3k views

Low-rank factorization of SPD matrix

I have a symmetric positive definite (SPD) matrix $A$ that needs to be factorized as ${A=SS^{T}}$. However, using the Cholesky decomposition for this purpose is prohibitive in terms of computational ...
3 votes
2 answers
2k views

Iterative methods for linear system with non-diagonally dominant matrix

I have a linear system \begin{align*} \left[\begin{array}{cccc} 1 & 2 & 1 & -1 \\ 3 & 2 & 4 & 4 \\ 4 & 4 & 3 & 4 \\ 2 & 0 &...
5 votes
1 answer
251 views

Smooth, non-analytic functions of non-normal matrices

My apologies if this isn't a well-enough-posed question, I think I'm partly unsure of what exact question to even ask. There are many different ways in which we can take a function of a matrix. We ...
3 votes
0 answers
147 views

Convolution integral and its matrix representation

My background is chemistry and I was exploring some one dimensional deconvolution problems i.e., resolution of two or more overlapping peaks. A lot of excellent work was done in the 1970-80s. However, ...
0 votes
1 answer
266 views

Using QR or SVD to sum up finite number of matrices

Problem I was wondering if there are any theoretical results that tackle the following problem: Construct the following matrices $\mathbf{\mathcal{S}_{1}},\mathbf{\mathcal{S}_{2}},\ldots,\mathbf{\...
0 votes
0 answers
227 views

Decomposition of symmetric block matrix

I came across this question and got really interested about it. There, the OP asks whether is possible to decompose a $2n \times 2n$ block matrix: $$ \begin{pmatrix} X & I \\ I & Y \end{...
2 votes
1 answer
164 views

The "best way" to order unknowns in linear systems

Start with a linear system of the form \begin{equation*} Ax + Bt + C = 0, \end{equation*} where $x = (x_1, \dots, x_n) \in \mathbb R^n$ is the vector of unknowns, $t \in \mathbb R^m$ is a vector of ...
1 vote
0 answers
192 views

What is the solution of the matrix equation $A X + X A' + B X B' + C = 0$ for $X$?

I know that the matrix equation $A X + X A' + C = 0$ is in the form of the time-continuous Lyapunov equation, so solving for $X$ is pretty trivial since the solution already and numeric solvers ...
3 votes
2 answers
246 views

A problem about determinant and matrix

Suppose $a_{0},a_{1},a_{2}\in\mathbb{Q}$, such that the following determinant is zero, i.e. $ \left |\begin{array}{cccc}\\ a_{0} &a_{1} & a_{2} \\ \\ a_{2} &a_{0}+a_{1} & a_{1}+a_{...
0 votes
1 answer
535 views

Conditions to solve linear system with matrix blocks

How to verify if a linear system of symmetrical matrix blocks has solution? I have the matrix: $\left[M\right]_{p \times p}$, symmetrical $\left[G\right]_{p \times q}$ and then, I would like to ...
0 votes
1 answer
230 views

Solution of complex linear system

In Brubeck, Nakatsukasa, and Trefethen - Vandermonde with Arnoldi (example 3) they solve the following linear system: $$\operatorname{Re}\left(\begin{array}{ccc}1 & \cdots & z_{1}^{n} \\ 1 &...
21 votes
3 answers
51k views

What is the time complexity of truncated SVD?

Full SVD, on an $m \times n$ matrix $A$, [U,S,V] = svd(A), would cost $O(m^2n + mn^2 + n^3)$ time. But what is the time complexity if we only need the $k$ largest ...
1 vote
1 answer
146 views

Norm of a matrix with clustered eigenvalues

On page 271 of Trefethen and Bau's Numerical Linear Algebra, it is constructed a matrix $$A=2I_{m\times m}+0.5\cdot\frac{\text{rand}(m)}{\sqrt{m}}$$ for $m=200$, where rand(m) is an array with $m\...
1 vote
1 answer
326 views

For the purposes of solving linear equations, is there a fast decomposition that works for all Hermitian matrices?

Let $A$ be an arbitrary Hermitian matrix. Is there a way of efficiently factorizing $A$ for the purposes of solving $Ax = b$ for arbitrary $b$? There are two decompositions I'm aware of that nearly ...
9 votes
1 answer
472 views

$M = AA^t$ where $A$ has unit norm columns

Let $M \in \mathbb{R}^{k\times k}$ positive definite with $\operatorname{tr} M = m$, where $m$ is an integer such that $m \geq k$. I have found a way (using this answer) to decompose $M = AA^t$ with $...
4 votes
2 answers
948 views

Numerically solving for pseudo inverse of non-squared Vandermonde matrix

I have a linear system to solve, set up as: $\bf{Ax}=\bf{b}$ with a non-squared matrix A, $ \bf{A}= \begin{bmatrix} 1 & A_{1} & A_{1}^2 & \cdots & A_{1}^n \\ 1 & A_{2} & A_{...
1 vote
0 answers
121 views

Algorithm for the nilpotence of matrix polynomials

Let $P$ be a multivariate polynomial of real-valued $N \times N$ matrices. Given $X_1, X_2, ..., X_M \in \mathcal{M}_N\{\mathbb{R}\}$, is there any optimal algorithm to determine whether the result of ...
1 vote
1 answer
321 views

Solve linear system with bordered positive definite matrix

I want to solve the usual $A x = b$ system. In block form: $$ \begin{bmatrix} B & c \\ c^{T} & 0 \end{bmatrix} \begin{bmatrix} x' \\ x_{n+1} \end{bmatrix} = \begin{bmatrix} b' \\ b_{n+1} \end{...
7 votes
2 answers
3k views

Factorizing a block symmetric matrix

Let $X,Y\in\mathbb{R}^{n\times n}$ be symmetric matrices. You may assume that $X$ is positive semidefinite and $Y$ negative semidefinite, if needed, but not that they are invertible. I would like to ...
12 votes
2 answers
9k views

What is the time complexity of the matrix exponential?

While trying to compute the Matrix Exponential of an $n \times n$ array I decided to take advantage of a Python function called scipy.linalg.expm(). According to ...
0 votes
0 answers
41 views

Orthogonality condition of symmetric matrix pencil

Let $P(\lambda)=\lambda M−L\in \mathbb{R}^{n \times n}$ be a matrix pencil with symmetric nonsingular matrix $M$ and $L$ is a weighted Laplacian matrix of a connected graph. Clearly $(0,1_n)$ is an ...
2 votes
0 answers
52 views

Large-scale projected minimum-eigenvalue computations

I am interested in efficient numerical procedures for solving large-scale instances of the following projected minimum-eigenvalue problem: $$\mu := \min_{v \in \mbox{ker}(A)} \frac{v^T H v}{\lVert v \...
6 votes
0 answers
141 views

Algorithm to check a conjectural value for the rank of a large matrix

Feel free to suggest a different title, I'm not sure how to phrase this. I'm in the following somewhat specific situation: I'm checking a conjecture which at the end of the day boils down to the ...
5 votes
1 answer
403 views

Best orthogonal approximation of rank 1 matrix

Let $X=\lambda_0u_0v_0^T\in\mathbb{R}^{n\times n}$ be a rank 1 matrix where $\lambda_0\in\mathbb{R}$, $u_0,v_0$ are of unit Euclidean norm. What is the solution of the following problem? $$\hat{X}=\...
9 votes
1 answer
1k views

Computation time of Smith normal form in Maple

I am using Maple to compute the Smith normal form (SNF) of a $120 \times 120$ matrix and it seems that I will never get an answer back. I have checked my code for small cases and I believe that it is ...
11 votes
1 answer
896 views

Decide if a matrix is transposable

A matrix $M$ is called transposable if it can be transformed into its transpose $M^t$ via row and column permutations. Is there an efficient a way/algorithm to decide if a given matrix is ...
3 votes
0 answers
244 views

An inequality concerning the solution of a Lyapunov equation

Let $A$ be an Hurwitz stable matrix (i.e. the real part of the eigenvalues of $A$ lie in the left-half plane) and $Q$ be a positive semidefinite matrix ($Q\ge 0$, for short). Let $P>0$ be the ...
4 votes
1 answer
296 views

Is there a fast algorithm to test positivity of all principal minors of non-symmetric matrix?

I have a matrix $A \in \mathbb{R}^{n \times n}$ with positive eigenvalues. In the symmetric case, Sylvester's criterion implies that all the principal minors are positive. In the non-symmetric case, ...
0 votes
1 answer
540 views

Computing spectrum of convex combination of SPD matrices given individual spectral decompositions

Given the spectral decompositions of a non-commuting collection of symmetric positive definite $N\times N$ matrices $$\left\{ K_{i}\right\} _{i=1}^{M}, U_{i}D_{i}U_{i}^{T}=K_{i},\quad i=1,\dots,M,$$ ...
5 votes
1 answer
260 views

Numerical minimization spectral norm under diagonal similarity

This question is a follow up. Let $A$ be a real square matrix of size $n \times n$. How to determine the minimum spectral norm under diagonal similarity, i.e., $$ s(A) = \inf_{D} \lVert D^{-1} A D\...
0 votes
1 answer
3k views

Cholesky decomposition – non-positive definite matrix

In order to pass the Cholesky decomposition, I understand the matrix must be positive definite. However, I also see that there are issues sometimes when the eigenvalues become very small but negative ...
11 votes
0 answers
764 views

Fast computation of matrix product $AXA^T$ with fixed $A$?

Suppose we have two $n$-by-$n$ matrices $X$ and $A$, where $A$ is known and $X$ may change in different invocations, and we want to compute $AXA^T$. Is there an algorithm that beats the naive one of ...
8 votes
1 answer
2k views

Finding Toeplitz matrix nearest to a given matrix

For an arbitrary $N\times N$ Hermitian matrix $A$, I want to derive a Toeplitz matrix from $A$ such that the eigenvectors of both matrices have minimal change. Specifically I want find the Toeplitz ...
7 votes
3 answers
1k views

Checking positive semi-definiteness of integer matrix

Key Problem : Is there any theorem about eigenvalues or positive semi-definiteness of small size matrices with small integer elements? I have to check positive semi-definiteness of many symmetric ...
1 vote
0 answers
19 views

Empirical approaches to validate observational bounds on minimum gap between least eigenvalues of $n \times n$ correlation matrix and its submatrices

Let $\Sigma$ be an $n \times n$ correlation matrix whose least eigenvalue is denoted by $\lambda$. $\Sigma_i'$ be an $(n-1) \times (n-1)$ submatrix of $\Sigma$ obtained by eliminating the $i$-th row ...
4 votes
3 answers
3k views

Is this inequality involving the Frobenius norm right?

Let $A$ be a generic (or varying) square, real $ n \times n$ matrix. Let $G$ be a fixed $n \times k$ matrix, $k < n.$ Denote by $||.||_F$ the Frobenius norm. Is it true that $||AG||_F \geq c(G) ||...
4 votes
0 answers
149 views

Zero diagonal nonsymmetric block checkerboard matrix: orbits and numerical ranges

Let $A \in \mathbb{R}^{m \times m}$ be a nonsymmetric zero diagonal matrix with a zero/non-zero pattern which is symmetric and persymmetric (i.e. symmetric in the northeast-to-southwest diagonal). If ...