Questions on the various algorithms used in linear algebra computations (matrix computations).

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3
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1answer
88 views

I want to study Numerical linear algebra [closed]

Would you like to recommend a book to me? the proof is explicit and easy to understand is preferred.
1
vote
0answers
47 views

Gaussian elimination vs. Jacobi iteration

How can I determine which of the matrix solver is faster for a given set of equations: Gaussian elimination or Jacobi iteration? In case, I have a banded matrix, is it advisable to use LU ...
1
vote
0answers
41 views

When is the LU decomposition unique?

I want to find out when a matrix decomposition $A = LU $ (L lower and U upper matrix) is unique? Clearly, if $A$ is not invertible, there is no chance that this decomposition is unique. Hence, ...
0
votes
1answer
46 views

Simplying linear equation to get quartic in q using Maple and then using Descarte’s rule of sign

Using the maple I am trying to get quardic in q from this big linear equation. Then use Descarte’s rule of signs to determine the number of positive roots. \begin{equation} ...
0
votes
1answer
42 views

Solve for a matrix in a linear equation

This is probably a really basic question, but we are stuck and the usual keyword lead to the normal "Solving linear equations with matrices"/Gaussian-elimination pages ... I have an equation $A X B + ...
2
votes
2answers
72 views

Determinant of an ill conditioned matrix

I have the following ill conditioned matrix. I want to find its determinant. How is it possible to calculate it without much error \begin{equation} \left[\begin{array}{cccccc} ...
0
votes
0answers
42 views

System of linrar equations and condition number

The relative error of the solution of a system of linear equation $Ax=b$, for any natural norm $\|\cdot\|$ is bounded by $$ \frac{1}{\| A\| \|A^{-1} \|} \frac{\|r\|}{\|b\|} \le \frac{\|e\|}{\|x\|} \le ...
0
votes
1answer
88 views

condition number of orthogonal matrix

Let $A\in M_n(\mathbb R)$ be an orthogonal matrix. Then: $cond (A) =1$. I tryed to use facts about the eigenvalues but is did not help. In 2-norm it is easy to prove it since $||A||_2 = \sqrt{\rho ...
0
votes
1answer
56 views

Spectral norm of a Hadamard product

Let $F$ be the $n\times n$ DFT matrix, i.e., $F_{i,j} = \exp\left(-\tfrac{2\pi(i-1)(j-1)}{n}\imath\right)$, for $1\le i,j\le n$ and $\imath =\sqrt{-1}$. Futhermore, let $\Vert \cdot\Vert$ and $\odot$ ...
0
votes
2answers
22 views

Finding a rotation matrix

I am looking for a rotation matrix such that $$ \operatorname{rot} \cdot \begin{pmatrix} -1 & 0 & 0 \\ 1 & -1 & 0 \\ 0 & 1 & -1 \\ 0 & 0 & 1 \end{pmatrix} = ...
1
vote
1answer
111 views

Efficient Algorithm for Iteratively Reweighted Least Squares Problem

I'm interested in solving a weighted least squares problem of the form $X^T W X \beta = X^T W Y$ where $W$ is a diagonal, positive definite matrix, $X \in R^{m \times n}$, $Y \in R^{m \times 1}$ and ...
3
votes
2answers
82 views

Power iteration

If $A$ is a matrix you can calculate its largest eigenvalue $\lambda_1$. What are the exact conditions under which the power iteration converges? Power iteration Especially, I often see that we ...
1
vote
1answer
44 views

Lipschitz continuity for generalized inverse matrix

Suppose $A$ and $B$ are full-rank and well-conditioned. Is Lipschitz continuity held for generalized inverse? $$\|A^+ - B^+\| \le \omega \|A-B\|,$$ for some $\omega > 0$, where the norm could ...
0
votes
1answer
16 views

LD$t(L)$ factorization and eigenvalues

A positive definite matrix $A$ can be factored in to $LDt(L)$form. Is the statement the eigenvalues of $A$ are the diagonals of $D$ true? If so , how to prove it?
3
votes
0answers
55 views

Does anyone know any reference for this matrix?

For $n \geq 4$, $A$ is $(n-1) \times (n-1)$ tridiagonal block matrix $$A = n^2 \begin{bmatrix}B & -I & 0 & \cdots & \\-I & B & -I & 0 & \\ 0 & -I & B & -I ...
2
votes
2answers
45 views

Solving $a_1x_1 + \cdots +a_nx_n = b$

I'm glad to ask my first question on the maths site! So here we go. I'm trying to set up prices right now and here is my problem : I know that my customer has a certain amount of money available. ...
2
votes
1answer
46 views

Can an iterative method converge for some initial approximation?

Studying iterative methods for solving(or approximating) linear equation systems, I came accross the following theorem$^1$: Let the following be an iterative method: $$x^{(0)},\qquad known\\ ...
2
votes
1answer
131 views

Inverse of constant matrix plus diagonal matrix

Is there an efficient way to calculate the inverse of an NxN diagonal matrix plus a constant term? I am looking at N of around 40000. $\left[\begin{array}{cccc} a & b & \cdots & b\\ b ...
2
votes
1answer
68 views

Linear equation: $(A^\top A+B^\top B + D)x=c$ where $A,B$ are structured sparse and $D$ is diagonal.

Updated: the goal is to solve $(A^\top A+B^\top B + D)x=c$. Maybe it is not necessary to compute $(A^\top A+B^\top B + D)^{-1}$. Denote $e=(1,1,\ldots,1)^\top\in\mathbb{R}^n$ and ...
1
vote
1answer
42 views

Consistency of the system $AX=b$

In the concept of consistency (compatibility) of a matrix, when $b \in \mathbb R (A)$ we know for sure that the system is consistent or there may exists no solution for it? But when $b \notin \mathbb ...
0
votes
2answers
29 views

Formatting Linear equation

How do I craft a linear equation so that it is in the form of $ax + bx + c = 0$ where $a^2 + b^2 = 1$ if I have two points? I know how to get it into the form $ax + bx + c = 0$ but I can't figure out ...
1
vote
0answers
36 views

Check feasibility of a system of integer linear equations

I'm currently working on a very large integer linear programme which cannot be solved within any reasonable time. The initial set of linear equations S={Ax<=b) is feasible. I want to add more ...
2
votes
0answers
53 views

Effective computation of matrix commutator

Is there a faster way to compute the commutator of large (at least one of them sparse) matrices $[A,B]$ then to compute $AB$ ,$BA$ and subtract them?
1
vote
0answers
32 views

Influence of preconditioning on degenerate eigenvectors

I'm using a hierarchical decomposition of a sparse matrix $A$ as suggested here. I find that the method essentially finds eigenvectors using the QR algorithm. $A$ has some eigenvalues with ...
1
vote
0answers
76 views

Newton's method for multidimensional functions

Can Newton's method be used to find the root of a function f : $\mathbb{R}^n\to\mathbb{R}^m$. Can anyone provide a proof for this? (I have checked the method of solving system of equations with ...
1
vote
1answer
62 views

Efficient method for determining to the most positive eigenvalue of a matrix

I am trying to implement an algorithm that requires knowing the largest $\textbf{positive}$ eigenvalue of a $\textbf{real symmetric, non-sparse}$ matrix and the corresponding eigenvector. The actual ...
0
votes
0answers
30 views

What is the largest (dense, real, symmetric) random matrix I can diagonalize on a computer?

I have read that 10.000x10.000 is no problem for LAPACK or similar routines. I would like to know if N=20.000 or 40.000 is possible. EDIT: I don't know if it is relevant, but the matrix is positive ...
0
votes
0answers
44 views

Strange Convergence of SOR/Gauss-Seidel

I am having trouble with the convergence of my Gauss-Seidel/SOR method. The matrix $A$ in $Ax=y$ seems to be positive-(semi)definite. Its eigenvalues are: However, the method (SOR) improves the cost ...
1
vote
0answers
40 views

Change in Singular Value Decomposition of a matrix on addition of a single row

Given that I know the svd decomposition of a matrix, is there any way to compute the svd decomposition of the matrix obtained by adding a single row to the original matrix? Is there any relation ...
1
vote
0answers
51 views

If symmetric matrix in a least-square deconvolution problem positive definite?

I want to apply Gauss-Seidel method in a least square deconvolution problem. The convolution of two vectors is written in: $h * x = z$. $$z(n) = \sum_{i=0}^{N-1}h(i)x(n-i)$$ It is a linear transform ...
1
vote
1answer
37 views

How to recover Q from the (tiled) QR decomposition using householder factorisation?

I'm trying to implement the tiled QR decomposition in MATLAB (in an attempt to understand it), and I'm trying to check that my SGEQRF (upper corner tiles) function is working correctly. I have a ...
0
votes
0answers
44 views

How to find a transformation matrix T?

(1.) Suppose there is matrix C of dimension "p by n" where p is less then n i.e. p I want to know is there any particular way exist to find transformation matrix T of dimension "n by n" such that ...
0
votes
2answers
37 views

Eigenvalues and eigenvectors of a matrix

We know that if $\lambda (\neq 0)$ is an eigenvalue of a matrix $A$ corresponding to eigenvector $X$, then $\dfrac{1}{\lambda}$ is an eigenvalue of $A^{-1}$. But whether the corresponding eigenvector ...
0
votes
0answers
27 views

Orthogonal polynomials induction proof

I tried writing this all out but cannot seem to get anything sensible. Basically I want to prove that assuming w(x) is the weight function of a Gram Schmidt orthogonalization process and w is an ...
2
votes
1answer
92 views

Matrix Norm Inequalities and Linear Least Squares

I am working through one of my universities old QUALS and came across the following problem: Let $A,E\in \mathbb{C}^{m\times m}$. Suppose that $\sigma_\min>0$ is the smallest singular value of ...
0
votes
2answers
48 views

Is this Gram-Scmidt (or an application of) it?

I am given a $2\times 2$ matrix $$\left[ \begin{array}{ccc} a & 0 \\ 0 & b \\ \end{array} \right] $$ where $a,b \in \mathbb{R}$. I was told than an orthnormal basis for the colums of this ...
0
votes
1answer
87 views

Matrix with constant row sum

It is well known (and shown several times on this site) that if we have a matrix so that each row sums to zero then the matrix must be singular. I am curious if the following partial converse is ...
3
votes
1answer
132 views

Prove $|\det A| \leq \prod_{j=1}^n ||a_j||$

Let's say A is a square n by n matrix. ||$x$||=$x^T x$ and x is a real n-column norm. How would you show this? I tried to use the QR factorization here in showing that ||$a_j$||=||$r_j$||, but ...
1
vote
1answer
24 views

Question regarding Givens Rotation

I need to solve the following equation using Givens Rotation: $$ A\cdot x = b $$ Correction: I need to solve: $$ ||A\cdot x - b || \to \min $$ with $$A = \begin{bmatrix} 1 & 1 \\ -2 & ...
1
vote
2answers
139 views

Trace minimization of a matrix

Suppose $S = \pmatrix{1&1\\ 1&0\\ 0&1}$, $W$ is a $3\times3$ covariance matrix, which could be regarded as fixed. I need to find a $2\times 3$ matrix $Q$ that minimizes $$ ...
3
votes
1answer
220 views

Numerical verification of solution.

I have the non-linear equation \begin{align} &\left( {x}^{2}-1 \right) \left( -\frac{1}{4}\left({\frac { \left( 4\,{x}^{3}+2\, ex \right) ^{2}}{ \left( {x}^{4}+e{x}^{2}+f \right) ...
2
votes
2answers
62 views

How to figure out the spectral radius of this matrix

$$A=\begin{array}{ccc} 0 & 1/2 & 0 & \cdots & 0 \\ 1/2 & 0 & 1/2 &\cdots& 0\\ 0 & 1/2 & 0 & \cdots & 0\\ \vdots & \vdots & \vdots &\ddots ...
1
vote
0answers
56 views

Numerical algorithm to solve quadratic eigenvalue problem.

Given the equation $$-4 \left(a^2+a (n-1) (2 t^2-1)\right) \left(\sum _{i=0}^n \alpha_i t^{2 i}\right)^2 \\ +\frac12 \left(\sum _{i=0}^n \alpha_i t^{2 i}\right) \left(t \left(8 a (t^2-1)+1\right) \sum ...
0
votes
1answer
62 views

Avoiding gimbal lock

I am not really sure if I understand the phenomenon of gimbal lock correctly. Say I have a vector $\begin{pmatrix} x\\ y\\ z \end{pmatrix}$. And I want to keep the vector's length fixed but move it ...
1
vote
1answer
144 views

Norm of Block Diagonal Matrix

Given a matrix $A \in R^{m \times n}$ with known upper bound on the operatornorm $\| A \|$ I want to find an upper bound for the operator norm of the square root of the following matrix that is given ...
7
votes
1answer
249 views

Fast algorithm for approximating Eigenvalue distribution of large sparse matrix

I am interested in the eigenvalue distribution of a huge $2^{16}$x$2^{16}$ Hermitian sparse matrix with spectrum contained in $[-1,1]$. That is I don't need to know all eigenvalues exactly, but rather ...
1
vote
1answer
72 views

Proof that eigenvector corresponding to simple eigenvalue is continuous

Let $\lambda$ be a simple eigenvalue of $A \in L(C^n)$ and let $x$ be the corresponding eigenvector. Then for $E \in L(C^n)$, $A+E$ has an eigenvalue $\lambda(E)$ and an eigenvector $x(E)$ such that ...
1
vote
1answer
25 views

linear systems&normalize

suppose $f: \mathbb{R}^n \rightarrow \mathbb{R}^n$ be a linear function which can be represented by a $n \times n$ matrix. Then the jacobian of $f$ is the same as the function for $f$. But I now want ...
1
vote
0answers
45 views

Kalman Filter Predict Update of LDL Decomposition of a Covariance Matrix

From the state predict equation: http://en.wikipedia.org/wiki/Kalman_filter# $$P_{n+1}=AP_nA^T + Q$$ Suppose the $LDL^{T}$ ( http://en.wikipedia.org/wiki/Cholesky_decomposition#LDL_decomposition_2 ) ...
1
vote
0answers
22 views

Algorithm for finding only the $k$-th singular vectors

I know that we have truncated SVD that can compute the first say $k$ largest singular values (and corresponding singular vectors). However, I'd like to know if there is an algorithm that can find only ...