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lecture_16
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| lecture_16 [2016/03/30 12:00] – rupert | lecture_16 [2017/03/30 09:20] (current) – [Chapter 3: Vectors and geometry] rupert | ||
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| + | === Example: $n=2$, general case === | ||
| + | |||
| + | If $A=\def\mat# | ||
| + | |||
| + | Recall that $AJ=(\det A)I_2=JA$; we calculated this earlier when we looked at the inverse of a $2\times 2$ matrix. Hence for a $2\times 2$ matrix $A$, if $\det A\ne0$, then $A^{-1}=\frac1{\det A}J$. | ||
| + | |||
| === Example: $n=3$ === | === Example: $n=3$ === | ||
| If $\def\mat# | If $\def\mat# | ||
| - | \[ C=\mat{ | + | \[\def\vm# |
| \vm{-4& | \vm{-4& | ||
| -\vm{1& | -\vm{1& | ||
| Line 29: | Line 35: | ||
| If again we take $A=\mat{3& | If again we take $A=\mat{3& | ||
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| + | ==== Example ($n=4$) ==== | ||
| + | |||
| + | Let $A=\mat{1& | ||
| + | |||
| + | Recall that a matrix with a repeated row or a zero row has determinant zero. | ||
| + | We have \[C=\mat{+\vm{2& | ||
| + | so \[J=C^T=\mat{24& | ||
| + | Since $A$ is lower triangular, its determinant is given by multiplying together its diagonal entries: $\det(A)=1\times 2\times 3\times 4=24$. (Note that even if $A$ was not triangular, $\det A$ can be easily found from the matrix of cofactors $C$ by summing the entries of $A$ multiplied by the entries of $C$ (i.e., the minors) along any row or column.) | ||
| + | |||
| + | So \[A^{-1}=\frac1{\det A}J = \frac1{24}\mat{24& | ||
| + | You should check that this really is the inverse, by checking that $AA^{-1}=I_4=A^{-1}A$. | ||
| + | ===== A more efficient way to find $A^{-1}$ ===== | ||
| + | |||
| + | Given an $n\times n$ matrix $A$, form the $n\times 2n$ matrix | ||
| + | \[ \def\m# | ||
| + | \begin{array}{@{} c|c {}@} % it does autodetection | ||
| + | #1 | ||
| + | \end{array} | ||
| + | \right]}\m{A& | ||
| + | and use [[EROs]] to put this matrix into [[RREF]]. One of two things can happen: | ||
| + | |||
| + | * Either you get a row of the form $[0~0~\dots~0~|~*~*~\dots~*]$ which starts with $n$ zeros. You can then conclude that $A$ is not invertible. | ||
| + | * Or you end up with a matrix of the form $\m{I_n& | ||
| + | |||
| + | ==== Examples ==== | ||
| + | |||
| + | * Consider $A=\def\mat# | ||
| + | \def\go# | ||
| + | \def\ar# | ||
| + | \ar{R2\to R2-2R1}\go{1& | ||
| + | \end{align*} Conclusion: $A$ is not invertible. | ||
| + | * Consider $A=\left[\mat{1& | ||
| + | \ar{R2\to R2-2R1}\go{1& | ||
| + | \ar{R1\to R1-3R1}\go{1& | ||
| + | \end{align*} Conclusion: $A$ is invertible and $A^{-1}=\left[\mat{7& | ||
| + | * Consider $A=\left[\mat{3& | ||
| + | \ar{R1\to R1+R2} | ||
| + | \go{1& | ||
| + | \ar{R2\to R2+2R1,\ R3\to R3-5R1} | ||
| + | \go{1& | ||
| + | \ar{R3\leftrightarrow R2} | ||
| + | \go{1& | ||
| + | \ar{R2\to R2+2R3} | ||
| + | \go{1& | ||
| + | \ar{R1\to R1+3R2,\ R3\to R3-10R2} | ||
| + | \go{1& | ||
| + | \ar{R2\to R2+R3} | ||
| + | \go{1& | ||
| + | \ar{R2\to -R2,\ R3\to -R3} | ||
| + | \go{1& | ||
| + | \end{align*} Conclusion: $A$ is invertible, and $A^{-1}=\left[\mat{4& | ||
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lecture_16.1459339259.txt.gz · Last modified: by rupert
