Inverse of Matrix
Inverse of Matrix
The inverse of a matrix A, exists if A is non-singular (i.e., ⏐A⏐ ≠ 0) and is given by the formula
A–1 = Adj (A) / |A|
The inverse of a matrix is always unique.
Adjoint of a Square Matrix
Let A=[aij] be any n × n matrix. The transpose B of the matrix B = [Aij]n x n, where Aij denotes the cofactor of element aij is called the adjoint of matrix A and is denoted by the symbol Adj A.
∴ Adj (A) = [cof (A)]T
Properties of Adjoint:
If A be any n-rowed square matrix, then (Adj A) A = A (Adj A) = ⏐A⏐ In
where In is the n × n identity matrix.
Rank of A Matrix
Rank is defined for any matrix Am × n (need not be square)
Some important concepts:
1. Submatrix of a Matrix: Suppose A is any matrix of the type m × n. Then a matrix obtained by leaving some rows and some columns from A is called a submatrix of A.
2. Rank of a Matrix: A number r is said to be the rank of a matrix A, if it possesses the following properties:
(a) There is at least one square sub-matrix of A of order r whose determinant is not equal to zero.
(b) If the matrix A contains any square sub-matrix of order (r + 1) and above, then the determinant of such a matrix should be zero.
Put together, property (a) and (b) give the definition of the rank of a matrix as the “order of the largest non-zero minor.”
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