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Matrices

1.5 Matrix Inversion

Definition of the matrix inverse, inverse of 2×2 via formula, inverse of n×n via adjoint matrix, singularity condition, and laws of matrix algebra.

1.5 Matrix Inversion

Definition 1.24: If AB = I and BA = I, then B is the inverse of A, written A−1. The inverse exists only if A is square and non-singular.

Inverse of a 2×2 Matrix

A = [a,b; c,d]  →  A−1 = 1det(A) · [d,−b; −c,a]
det(A) = ad − bc must be ≠ 0. If det(A) = 0, A is singular and has no inverse.

Example 1.15: A = [[8,2],[4,3]]

det(A) = 24−8 = 16
A−1 = 116 ×
3−2
−48

Inverse of n×n Matrix via Adjoint

A−1 = adj(A)det(A)  where  adj(A) = CT (transpose of cofactor matrix)

Example 1.16: A = [[1,2,3],[7,5,6],[4,8,9]]

Step 1: Cofactor matrix C
−3−3936
6−30
−315−9
Step 2: adj(A) = CT
−36−3
−39−315
360−9
Step 3: det(A) = 1(−3) − 2(63−24) + 3(56−20) = −3 − 78 + 108 = 27
Step 4: A−1 = adj(A)27
−1929−19
−139−1959
430−13

1.6 Laws of Matrix Algebra

  • If AB = I then B = A−1 and A = B−1
  • (A−1)−1 = A
  • (kA)−1 = k−1A−1
  • (AT)−1 = (A−1)T
  • det(A−1) = 1det(A)
  • (AB)−1 = B−1A−1 (reverse order!)
Warning: (AB)−1 = B−1A−1 NOT A−1B−1 — order is reversed!

Example 1.17: If BACD = I, express A in terms of inverses.
B−1BACD = ACD = B−1 → AC = B−1D−1 → A = B−1D−1C−1