
Inverse of a Matrix
Unlike numbers, the division operation is not defined for matrices. A similar (but not same) operation is to find the inverse of a matrix. Note that only square matrices can have inverses. When a square matrix is nonsingular (), its inverse exists () and is unique.
Consider the number . When we multiply any number by , we get the same number and when we divide a number by , we get its reciprocal.
Similarly, we have identity matrix . When we multiply any matrix by (with appropriate order), we get the same matrix. When we multiply a matrix by its inverse, we get the identity matrix. Thus,
For a matrix , we have . If we do , we get , which is a identity matrix.

Finding the Inverse Using Row Transformations
We know
By some means, if we reduce to , LHS will become , which is . The matrix on the RHS will have to undergo the same set of transformations in same order, as we did on to get .
The identity matrix on the right hand side will now get transformed to . Thus,
To find inverse of a matrix using row transformations:
1) Make sure that the determinant of the matrix is nonzero.
2) Make by using transformation of the kind
3) Make all other elements in the 1st column by using transformations
4) Make by using transformation of the kind
5) Make all other elements in the 2nd column by using transformations
To find inverse of a matrix using row transformations:
1) Make sure that the determinant of the matrix is nonzero.
2) Make by using transformation of the kind
3) Make all other elements in the 1st column by using transformations
4) Make by using transformation of the kind
5) Make all other elements in the 2nd column by using transformations
6) Make by using transformation of the kind
7) Make all other elements in the 3rd column by using transformations
Notice the order by which we are transforming the given matrix into identity matrix. By performing the same sequence of transformations on identity matrix on the other side, we get the inverse.

Finding the Inverse Using Column Transformations
To find inverse of a matrix using column transformations:
1) Make sure that the determinant of the matrix is nonzero.
2) Make by using transformation of the kind
3) Make all other elements in the 1st row by using transformations
4) Make by using transformation of the kind
5) Make all other elements in the 2nd row by using transformations
To find inverse of a matrix using column transformations:
1) Make sure that the determinant of the matrix is nonzero.
2) Make by using transformation of the kind
3) Make all other elements in the 1st row by using transformations
4) Make by using transformation of the kind
5) Make all other elements in the 2nd row by using transformations
6) Make by using transformation of the kind
7) Make all other elements in the 3rd row by using transformations

Finding the Inverse by Adjoint Method
is given by
The adjoint of A is a matrix obtained as follows:
1) Obtain .
2) Obtain the matrix of minors. The minor of an element is obtained by eliminating th row and th column and finding the determinant of the newly formed matrix. Knowing the concept of minor is essential. We will define the rank of matrix using this.
3) Obtain the matrix of cofactors. The cofactor of an element is
4) Take the transpose of matrix of cofactors. Transpose of a matrix is obtained by interchanging the rows and columns. This will be the adjoint. Thus,
There is another method to find the inverse, which is using matrices in normal form. We will see this method in }.

Solving a System of Simultaneous Equations Using Matrices
Consider the following system of equations:
We want to find the values of and , which will satisfy all 3 equations simultaneously. This system of equations can be written in matrix form as
Let us call the matrix , the matrix on the RHS and the matrix of unknowns . Thus, we have
There are 2 methods of solving this:

Method 1 : Method of Inversion
In the method of inversion, we find the inverse of the matrix of the coefficients. \\
We know that . On premultiplying both sides of by , we get , i.e. i.e. .
So, all we have to do is first find the inverse of and then premultiply by $A^{1}$.
In this example,
So,
Thus, and .

Method 2 : Method of Reduction
In this method, we reduce to an uppertriangular matrix by performing row operations. Same operations are to be performed on matrix in same sequence. Ultimately, we are left with following matrix:
So, we obtain from the last row, then we get from the 2nd row and then, from the 1st row.
[Note – Try it and see whether you get the same values o $x,y$ and $z$ as by inversion method.]