Proba ML
7. Linear Algebra
7.3 Matrix Inversion

7.3 Matrix inversion

7.3.1 Square matrix

The inverse of a square matrix A∈RnA \in \mathbb{R}^n is A−1A^{-1}. It is the unique matrix such that:

AA−1=I=A−1AA A^{-1}=I=A^{-1}A

A−1A^{-1} is only defined if det(A)≠0\mathrm{det}(A)\neq 0, that is if AA is not singular.

Some properties:

(A−1)−1=A(AB)−1=B−1A−1(A−1)⊤=(A⊤)−1≜A−⊤\begin{align}(A^{-1})^{-1}&=A \\ (AB)^{-1}&=B^{-1}A^{-1} \\ (A^{-1})^\top &= (A^\top)^{-1}\triangleq A^{-\top} \end{align}

For a simple 2x2 matrix, we have:

A=[abcd],    A−1=1∣A∣[d−b−ca]A=\begin{bmatrix}a & b \\c &d\end{bmatrix},\;\;A^{-1}=\frac{1}{|A|}\begin{bmatrix}d & -b \\-c &a\end{bmatrix}

For a block diagonal matrix, we invert each block separately:

[A00B]−1=[A—100B—1]\begin{bmatrix}A & 0 \\0 &B\end{bmatrix}^{-1}=\begin{bmatrix}A^{—1} & 0 \\0 &B^{—1}\end{bmatrix}