Properties of a Singular Matrix

The following are the properties of the Singular Matrix:

• Every singular matrix must be a square matrix, i.e., a matrix that has an equal number of rows and columns.
• Determinant of a singular matrix is equal to zero.
• As the determinant of a singular matrix is zero, its inverse is not defined.
• A zero matrix of any order matrix is a singular matrix, as its determinant is zero.
• In a singular matrix, some rows and columns are linearly dependent.
• Rank of a singular matrix will be less than the order of the matrix, i.e., Rank (A) < Order of A.
• A matrix that has any two rows or any two columns identical is singular, as the determinant of such a matrix is zero.
• When a row or column’s elements in a matrix are all zeros, then the matrix is singular, as its determinant is zero.
• When one row (or column) of a matrix is a scalar multiple of another row (or column), then the matrix is singular as its determinant is zero. 

Singular Matrix: A singular matrix is a square matrix of determinant “0.” i.e., a square matrix A is singular if and only if det A = 0. Inverse of a matrix A is found using the formula A^-1 = (adj A) / (det A). Thus, a matrix is called a square matrix if its determinant is zero.

Now let us discuss about singular matrix, its properties, and others in detail.