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;