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[2020-02-05 Wed 21:19]
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Session 11: Matrix Inverses | Part B: Matrices and Systems of Equations | 1. Vectors and Matrices | Multivariable Calculus | Mathematics | MIT OpenCourseWare

1 Chalkboard

Figure 1: Inverse Matrix

Figure 1: Inverse Matrix

Figure 2: Inverse Matrix formula

Figure 2: Inverse Matrix formula

Figure 3: Inverse Matrix Formula: Minors and cofactors

Figure 3: Inverse Matrix Formula: Minors and cofactors

Figure 4: Inverse Matrix Formula: Transpose and Divide by \(\det(A)\)

Figure 4: Inverse Matrix Formula: Transpose and Divide by \(\det(A)\)

2 How can we solve a small squared linear system?

2.1 Front

How can we solve a small squared linear system?

  • Low dimensional
  • \(2 \times 2\) system, or \(3 \times 3\) system
  • \(x_1 = a_{11}y_1 + a_{12}y_2 + a_{13}y_{3}\)
  • \(x_2 = a_{21}y_1 + a_{22}y_2 + a_{23}y_{3}\)
  • \(x_3 = a_{31}y_1 + a_{32}y_2 + a_{33}y_{3}\)

2.2 Back

  • Using inverse matrices
  • \(A \vb{x} = \vb{b}\)
  • \(A\) matrix with coefficients \((a_{ij})\)
  • \({\displaystyle \vb{x} = \begin{pmatrix} x_1 \ x_2 \x_3 \end{pmatrix}}\)
  • \({\displaystyle \vb{b} = \begin{pmatrix} b_1 \ b_2 \ b_3 \end{pmatrix}}\)

Solving (multiplying by inverse matrix \(M\) at the left)

\begin{align*} A \vb{x} &= \vb{b} \\\ M (A \vb{x}) &= M \vb{b}\\\ \vb{x} = M \vb{b} \end{align*}

3 When can we say that the inverse matrix of \(A\) exits?

3.1 Front

When can we say that the inverse matrix of $A$ exits?

3.2 Back

  • \(M\) is the inverse matrix of \(A\)
  • \(M \text{ exists } \Leftrightarrow \det(A) \neq 0\)
  • That’s because of determinant law of matrix multiplication
    • \(\det(AB) = \det(A) \det(B)\)
    • \(MA = I \implies \det(M)\det(A) = \det(I) = 1 \implies \det(A) \neq 0\)

4 Which step do we need to calculate a matrix inverse?

4.1 Front

Which step do we need to calculate a matrix inverse?

Set \(A\) matrix, and \(A^{-1}\) as inverse matrix

4.2 Back

  1. \(A\) is a \(n \times n\) matrix
  2. \(\det(A) \neq 0\)
  3. Unique solution
    • \(A^{-1}A = AA^{-1} = I\), Identity matrix
    • \(A \vb{x} = \vb{b}\)
    • \(M(A \vb{x}) = M \vb{b}\)
    • \(\vb{x} = M\vb{b}\)
  4. \({\displaystyle A^{-1} = \frac{1}{\det(A)} \text{adj}(A) = \frac{1}{\det(A)} \begin{pmatrix} A_{11} & A_{12} & A_{13} \ A_{21} & A_{22} & A_{23} \ A_{31} & A_{32} & A_{33} \end{pmatrix}^{T}}\)
    • \(\text{adj}(A)\), is the adjoint or adjugate of \(A\)
    • \(A_{ij} = (-1)^{i+j} \abs{A_{ij}}\) is the ij-cofactors
    • \(\abs{A_{ij}}\) is the ij-minor, the determinant after remove the row \(i\) and column \(j\)

Formula steps

  1. Calculate the matrix of minors
  2. Change the signs of the entries according to the checkerboard rule
  3. Transpose the resulting matrix, this gives \(\text{adj}(A)\)
  4. Divide every entry by \(\abs{A}\)

5 What is the quick formula for inverse of \(2 \times 2\) matrix \(A\)?

5.1 Front

What is the quick formula for inverse of $2 \times 2$ matrix $A$?

\({\displaystyle A = \begin{pmatrix}a & b \ c & d\end{pmatrix}}\)

5.2 Back

  • Cofactors \({\displaystyle \begin{pmatrix}d & -c \ -b & a \end{pmatrix}}\)
  • adj \(A\): \({\displaystyle \begin{pmatrix}d & -b \ -c & a \end{pmatrix}}\)
  • inverse of \(A\): \({\displaystyle \frac{1}{\abs{A}} \begin{pmatrix}d & -b \ -c & a \end{pmatrix}}\)

Steps:

  1. Switch \(a\) and \(d\)
  2. Change the signs on \(b\) and \(c\)
  3. Divide by the determinant