Illustrating matrix transpose rules in matrix multiplication
August 01, 2011 at 01:34 PM | categories: linear algebra | View Comments
Illustrating matrix transpose rules in matrix multiplication
John Kitchin
Contents
Rules for transposition
Here are the four rules for matrix multiplication and transposition
1. 
2. 
3. 
4. 
reference: Chapter 7.2 in Advanced Engineering Mathematics, 9th edition. by E. Kreyszig.
The transpose in Matlab
there are two ways to get the transpose of a matrix: with a notation, and with a function
A = [[5 -8 1];
[4 0 0]]
A =
5 -8 1
4 0 0
function
transpose(A)
ans =
5 4
-8 0
1 0
notation
A.' % note, these functions only provide the non-conjugate transpose. If your % matrices are complex, then you want the ctranspose function, or the % notation A' (no dot before the apostrophe). For real matrices there is no % difference between them. % below we illustrate each rule using the different ways to get the % transpose.
ans =
5 4
-8 0
1 0
Rule 1
m1 = (A.').'
A
all(all(m1 == A)) % if this equals 1, then the two matrices are equal
m1 =
5 -8 1
4 0 0
A =
5 -8 1
4 0 0
ans =
1
Rule 2
B = [[3 4 5];
[1 2 3]];
m1 = transpose(A+B)
m2 = transpose(A) + transpose(B)
all(all(m1 == m2)) % if this equals 1, then the two matrices are equal
m1 =
8 5
-4 2
6 3
m2 =
8 5
-4 2
6 3
ans =
1
Rule 3
c = 2.1;
m1 = transpose(c*A)
m2 = c*transpose(A)
all(all(m1 == m2)) % if this equals 1, then the two matrices are equal
m1 =
10.5000 8.4000
-16.8000 0
2.1000 0
m2 =
10.5000 8.4000
-16.8000 0
2.1000 0
ans =
1
Rule 4
B = [[0 2];
[1 2];
[6 7]]
m1 = (A*B).'
m2 = B.'*A.'
all(all(m1 == m2)) % if this equals 1, then the two matrices are equal
B =
0 2
1 2
6 7
m1 =
-2 0
1 8
m2 =
-2 0
1 8
ans =
1
m3 = A.'*B.' % you can see m3 has a different shape than m1, so there is no way they can % be equal.
m3 =
8 13 58
0 -8 -48
0 1 6
% categories: Linear algebra % tags: math % post_id = 552; %delete this line to force new post;