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Find the inverse of matrices in Exercise 29-32, if they exist. Use the algorithm introduced in this section.

\(\left( {\begin{aligned}{*{20}{c}}{\bf{1}}&{\bf{0}}&{ - {\bf{2}}}\\{ - {\bf{3}}}&{\bf{1}}&{\bf{4}}\\{\bf{2}}&{ - {\bf{3}}}&{\bf{4}}\end{aligned}} \right)\)

Short Answer

Expert verified

\(\left( {\begin{aligned}{*{20}{c}}8&3&1\\{10}&4&1\\{\frac{7}{2}}&{\frac{3}{2}}&{\frac{1}{2}}\end{aligned}} \right)\)

Step by step solution

01

Find the expression \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\)

\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&0&{ - 2}\\{ - 3}&1&4\\2&{ - 3}&4\end{aligned}\,\,\,\begin{aligned}{*{20}{c}}1&0&0\\0&1&0\\0&0&1\end{aligned}} \right)\)

02

Apply the row operation to the matrix \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\)

At row three, multiply row one by 2 and subtract it from row three, i.e., \({R_3} \to {R_3} - 2{R_1}\).

\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&0&{ - 2}\\{ - 3}&1&4\\0&{ - 3}&8\end{aligned}\,\,\,\begin{aligned}{*{20}{c}}1&0&0\\0&1&0\\{ - 2}&0&1\end{aligned}} \right)\)

03

Apply row operation to the matrix \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\)

At row two, multiply row one by 3 and add it to row two, i.e., \({R_2} \to {R_2} + 3{R_1}\).

\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&0&{ - 2}\\0&1&{ - 2}\\0&{ - 3}&8\end{aligned}\,\,\,\begin{aligned}{*{20}{c}}1&0&0\\3&1&0\\{ - 2}&0&1\end{aligned}} \right)\)

04

Apply row operation to the matrix \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\)

At row three, multiple row two by 3 and add it to row three, i.e., \({R_3} \to {R_3} + 3{R_2}\).

\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&0&{ - 2}\\0&1&{ - 2}\\0&0&2\end{aligned}\,\,\,\begin{aligned}{*{20}{c}}1&0&0\\3&1&0\\7&3&1\end{aligned}} \right)\)

05

Apply row operation to the matrix \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\)

At row two, add rows two and three, i.e., \({R_2} \to {R_2} + {R_3}\).

\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&0&{ - 2}\\0&1&0\\0&0&2\end{aligned}\,\,\,\begin{aligned}{*{20}{c}}1&0&0\\{10}&4&1\\7&3&1\end{aligned}} \right)\)

06

Apply row operation to the matrix \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\)

At row one, add rows three and one, i.e., \({R_1} \to {R_1} + {R_2}\).

\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&0&0\\0&1&0\\0&0&2\end{aligned}\,\,\,\begin{aligned}{*{20}{c}}8&3&1\\{10}&4&1\\7&3&1\end{aligned}} \right)\)

Divide row three by 2, i.e., \({R_3} \to \frac{{{R_3}}}{2}\).

\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&0&0\\0&1&0\\0&0&1\end{aligned}\,\,\,\begin{aligned}{*{20}{c}}8&3&1\\{10}&4&1\\{\frac{7}{2}}&{\frac{3}{2}}&{\frac{1}{2}}\end{aligned}} \right)\)

So, the inverse of the matrix is \(\left( {\begin{aligned}{*{20}{c}}8&3&1\\{10}&4&1\\{\frac{7}{2}}&{\frac{3}{2}}&{\frac{1}{2}}\end{aligned}} \right)\).

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Most popular questions from this chapter

If \(A = \left( {\begin{aligned}{*{20}{c}}1&{ - 2}\\{ - 2}&5\end{aligned}} \right)\) and \(AB = \left( {\begin{aligned}{*{20}{c}}{ - 1}&2&{ - 1}\\6&{ - 9}&3\end{aligned}} \right)\), determine the first and second column of B.

Suppose \({A_{{\bf{11}}}}\) is invertible. Find \(X\) and \(Y\) such that

\[\left[ {\begin{array}{*{20}{c}}{{A_{{\bf{11}}}}}&{{A_{{\bf{12}}}}}\\{{A_{{\bf{21}}}}}&{{A_{{\bf{22}}}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&{\bf{0}}\\X&I\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{A_{{\bf{11}}}}}&{\bf{0}}\\{\bf{0}}&S\end{array}} \right]\left[ {\begin{array}{*{20}{c}}I&Y\\{\bf{0}}&I\end{array}} \right]\]

Where \(S = {A_{{\bf{22}}}} - {A_{21}}A_{{\bf{11}}}^{ - {\bf{1}}}{A_{{\bf{12}}}}\). The matrix \(S\) is called the Schur complement of \({A_{{\bf{11}}}}\). Likewise, if \({A_{{\bf{22}}}}\) is invertible, the matrix \({A_{{\bf{11}}}} - {A_{{\bf{12}}}}A_{{\bf{22}}}^{ - {\bf{1}}}{A_{{\bf{21}}}}\) is called the Schur complement of \({A_{{\bf{22}}}}\). Such expressions occur frequently in the theory of systems engineering, and elsewhere.

Show that if ABis invertible, so is B.

In Exercises 1 and 2, compute each matrix sum or product if it is defined. If an expression is undefined, explain why. Let

\(A = \left( {\begin{aligned}{*{20}{c}}2&0&{ - 1}\\4&{ - 5}&2\end{aligned}} \right)\), \(B = \left( {\begin{aligned}{*{20}{c}}7&{ - 5}&1\\1&{ - 4}&{ - 3}\end{aligned}} \right)\), \(C = \left( {\begin{aligned}{*{20}{c}}1&2\\{ - 2}&1\end{aligned}} \right)\), \(D = \left( {\begin{aligned}{*{20}{c}}3&5\\{ - 1}&4\end{aligned}} \right)\) and \(E = \left( {\begin{aligned}{*{20}{c}}{ - 5}\\3\end{aligned}} \right)\)

\(A + 2B\), \(3C - E\), \(CB\), \(EB\).

Let T be a linear transformation that maps \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\). Is \({T^{ - 1}}\) also one-to-one?

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