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Questions tagged [matrix-decomposition]

Questions about matrix decompositions, such as the LU, Cholesky, SVD (Singular value decomposition) and eigenvalue-eigenvector decomposition.

209 votes
8 answers
119k views

Intuitively, what is the difference between Eigendecomposition and Singular Value Decomposition?

I'm trying to intuitively understand the difference between SVD and eigendecomposition. From my understanding, eigendecomposition seeks to describe a linear transformation as a sequence of three basic ...
user541686's user avatar
  • 13.9k
65 votes
4 answers
35k views

How unique are $U$ and $V$ in the singular value decomposition $A=UDV^\dagger$?

According to Wikipedia: A common convention is to list the singular values in descending order. In this case, the diagonal matrix $\Sigma$ is uniquely determined by $M$ (though the matrices $U$ and ...
capybaralet's user avatar
  • 1,285
40 votes
6 answers
33k views

How can you explain the Singular Value Decomposition to non-specialists?

In two days, I am giving a presentation about a search engine I have been making the past summer. My research involved the use of singular value decompositions, i.e., $A = U \Sigma V^T$. I took a high ...
Sidd Singal's user avatar
  • 3,462
35 votes
3 answers
35k views

How is the null space related to singular value decomposition?

It is said that a matrix's null space can be derived from QR or SVD. I tried an example: $$A= \begin{bmatrix} 1&3\\ 1&2\\ 1&-1\\ 2&1\\ \end{bmatrix} $$ I'm convinced that QR (more ...
whitegreen's user avatar
  • 1,613
34 votes
1 answer
29k views

Computing the Smith Normal Form

Let $A_R$ be the finitely generated abelian group, determined by the relation-matrix $$R := \begin{bmatrix} -6 & 111 & -36 & 6\\ 5 & -672 & 210 & 74\\ 0 & -255 &...
Euden's user avatar
  • 551
34 votes
6 answers
2k views

Proof that $\text{det}(AB) = \text{det}(A)\text{det}(B)$ without explicit expression for $\text{det}$

Overview I am seeking an approach to linear algebra along the lines of Down with the determinant! by Sheldon Axler. I am following his textbook Linear Algebra Done Right. In these references the ...
Jagerber48's user avatar
  • 1,461
31 votes
1 answer
59k views

When does a Square Matrix have an LU Decomposition?

When can we split a square matrix (rows = columns) into it’s LU decomposition? The LUP (LU Decomposition with pivoting) always exists; however, a true LU decomposition does not always exist. How do ...
Highrule's user avatar
  • 411
30 votes
2 answers
25k views

LU Decomposition vs. Cholesky Decomposition

What is the difference between LU Decomposition and Cholesky Decomposition about using these methods to solving linear equation systems? Could you explain the difference with a simple example? Also ...
mertyildiran's user avatar
28 votes
7 answers
15k views

Understanding the singular value decomposition (SVD)

Please, would someone be so kind and explain what exactly happens when Singular Value Decomposition is applied on a matrix? What are singular values, left singular, and right singular vectors? I know ...
Celdor's user avatar
  • 681
27 votes
5 answers
4k views

Let $A=(a_{ij})$ be an $n\times n$ matrix. Suppose that $A^2$ is diagonal. Must $A$ be diagonal?

Let $A=(a_{ij})$ be an $n\times n$ matrix. Suppose that $A^2$ is diagonal? Must $A$ be diagonal. In other words, is it true that $$A^{2}\;\text{is diagonal}\;\Longrightarrow a_{ij}=0,\;i\neq j\;\;?...
Medo's user avatar
  • 3,144
27 votes
4 answers
11k views

Is it true that any matrix can be decomposed into product of rotation, reflection, shear, scaling and projection matrices?

It seems to me that any linear transformation in ${\Bbb R}^{n \times m}$ is just a series of applications of rotation — actually i think any rotation can be achieved by applying two reflections, but ...
Sunny88's user avatar
  • 1,079
26 votes
8 answers
26k views

Relation between Cholesky and SVD

When we have a symmetric matrix $A = LL^*$, we can obtain L using Cholesky decomposition of $A$ ($L^*$ is $L$ transposed). Can anyone tell me how we can get this same $L$ using SVD or Eigen ...
Gatsu's user avatar
  • 325
23 votes
2 answers
7k views

The benefit of LU decomposition over explicitly computing the inverse

I'm going to teach a linear algebra course in the fall, and I want to motivate the topic of matrix factorizations such as the LU decomposition. A natural question one can ask is, why care about this ...
user avatar
22 votes
1 answer
3k views

How to understand the spectral decomposition geometrically?

Let $A$ be a $k\times k$ positive definite symmetric matrix. By spectral decomposition, we have $$A = \lambda_1e_1e_1'+ ... + \lambda_ke_ke_k'$$ and $$A^{-1} = \sum_{i=1}^k\frac{1}{\lambda_i}...
Jill Clover's user avatar
  • 4,827
20 votes
3 answers
3k views

Why is there not a test for diagonalizability of a matrix

Let $A$ be square.This question is a bit opinion based, unless there is a technical answer.I think it is helpful tho. Also this question is closely related to this question : quick way to check if a ...
Mahammad Yusifov's user avatar

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