Differences between revisions 1 and 4 (spanning 3 versions)
Revision 1 as of 2022-03-16 04:04:09
Size: 1031
Comment:
Revision 4 as of 2023-07-03 04:44:24
Size: 1110
Comment:
Deletions are marked like this. Additions are marked like this.
Line 1: Line 1:
= MatrixTransposition = = Matrix Transposition =

<<TableOfContents>>

-----
Line 7: Line 11:
The transpose of a matrix is a flipped version. The transpose of a matrix is a flipped version. The transpose of A is usually denoted A^T^; some notations, especially programming languages, instead use A'.
Line 10: Line 14:
┌ ┐ ┌ ┐
│ 1 2│ │ 1 3│
│ 3 4│ -> │ 2 4│
└ ┘ └ ┘
julia> A = [1 2; 3 4]
2×2 Matrix{Int64}:
 1 2
 3 4

julia> A'
2×2 adjoint(::Matrix{Int64}) with eltype Int64:
 1 3
 2 4
Line 16: Line 25:
The transpose of A is denoted A^T^. More formally, cell (''i'',''j'') of A^T^ is equal to cell (''j'',''i'') of A.

----
Line 20: Line 31:
== Multiplication of Transposed Matrices == == Notable Properties ==
Line 24: Line 35:
Inversion and transposition can be done in any order: (A^-1^)^T^ = (A^T^)^-1^.

----
Line 26: Line 40:
== Inverses of Transposed Matrices ==
Line 28: Line 41:
A simple proof based on the definition of inverse matrices and the above multiplicative property: == Symmetric Matrices ==
Line 30: Line 43:
{{{
      -1 -1
   A A = I = A A
A '''symmetric matrix''' is is any matrix that is equal to its transpose.
Line 34: Line 45:
(leave the left side off for now) Only square matrices (''n'' by ''n'') can be symmetric. However, multiplying a rectangular matrix R by its transpose R^T^ will always create a symmetric matrix. This can be proven with the above property:
Line 36: Line 47:
      -1
   A A = I

       T
     -1 T
  A A = I

       T
     -1
  A A = I

   T
 -1 T
A A = I

(bring back the left side)

   T
 -1 T -1
A A = I = A A

(and it should now be clear that)

   T -1
 -1 T
A = A
}}}

Inverses and transposes can be done in any order.
(R^T^ R)^T^ = R^T^ (R^T^)^T^ = R^T^ R

Matrix Transposition


Introduction

The transpose of a matrix is a flipped version. The transpose of A is usually denoted AT; some notations, especially programming languages, instead use A'.

julia> A = [1 2; 3 4]
2×2 Matrix{Int64}:
 1  2
 3  4

julia> A'
2×2 adjoint(::Matrix{Int64}) with eltype Int64:
 1  3
 2  4

More formally, cell (i,j) of AT is equal to cell (j,i) of A.


Notable Properties

The transpose of a product is the same as the reversed product of the transposed multiples. (A B)T = BT AT.

Inversion and transposition can be done in any order: (A-1)T = (AT)-1.


Symmetric Matrices

A symmetric matrix is is any matrix that is equal to its transpose.

Only square matrices (n by n) can be symmetric. However, multiplying a rectangular matrix R by its transpose RT will always create a symmetric matrix. This can be proven with the above property:

(RT R)T = RT (RT)T = RT R


CategoryRicottone

LinearAlgebra/MatrixTransposition (last edited 2024-01-27 21:22:51 by DominicRicottone)