If we have a matrix
![A = [ row 1: 2 , 3 row 2: -4 , -5 ]](/sites/default/files/images/06-matrices-07.gif)
We can't write
-- a result would require division.
So... Can we find
?
We sure can! It's called an inverse matrix. Here's how you find it:
Let's start with this matrix
![A = [ row 1: 2 , 3 row 2: -4 , -5 ]](/sites/default/files/images/06-matrices-10.gif)
This is going to work a lot like Gaussian elimination. (If you've ever seen that before.)
We make a big double matrix
![[ row 1: 2 , 3 row 2: -4 , -5 | row 1: 1 , 0 row 2: 0 , 1 ]](/sites/default/files/images/06-matrices-11.gif)
A on this side... the identity on this side.
The goal is to use row operations (like you did with Gaussian elimination) to...
![[ row 1: 2 , 3 row 2: -4 , -5 | row 1: 1 , 0 row 2: 0 , 1 ] ... turn the left half into I ... and, in the process, the right half with turn into A^( -1 )](/sites/default/files/images/06-matrices-12.gif)