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Find the inverses of the matrices in Exercises 29–32, if they exist. Use the algorithm introduced in this section.

29. \(\left( {\begin{aligned}{*{20}{c}}1&2\\4&7\end{aligned}} \right)\)

Short Answer

Expert verified

The inverse of the matrix is \(\left( {\begin{aligned}{*{20}{c}}{ - 7}&2\\4&{ - 1}\end{aligned}} \right)\).

Step by step solution

01

Write the algorithm for obtaining \({A^{ - 1}}\)

The inverse of an\(m \times m\)matrix A can be computed using theaugmented matrix \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\), where\(I\)is the identity matrix. Matrix Ahas an inverse if \(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\) is row equivalent to \(\left( {\begin{aligned}{*{20}{c}}I&{{A^{ - 1}}}\end{aligned}} \right)\).

02

Obtain the inverse of matrix A

Consider the matrix\(A = \left( {\begin{aligned}{*{20}{c}}1&2\\4&7\end{aligned}} \right)\).

Write the augmented matrix\(\left( {\begin{aligned}{*{20}{c}}A&I\end{aligned}} \right)\)as shown below:

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

Row reduce the augmented matrix.

Use the\({x_1}\)term in the first equation to eliminate the\(4{x_1}\)term from the second equation. Add\( - 4\)times row two to row two.

\(\left( {\begin{aligned}{*{20}{c}}1&2&1&0\\4&7&0&1\end{aligned}} \right) \sim \left( {\begin{aligned}{*{20}{c}}1&2&1&0\\0&{ - 1}&{ - 4}&1\end{aligned}} \right)\)

Use the\( - {x_2}\)term in the second equation to eliminate the\(2{x_2}\)term from the first equation. Add 2 times row two to row one.

\(\left( {\begin{aligned}{*{20}{c}}1&2&1&0\\0&{ - 1}&{ - 4}&1\end{aligned}} \right) \sim \left( {\begin{aligned}{*{20}{c}}1&0&{ - 7}&2\\0&{ - 1}&{ - 4}&1\end{aligned}} \right)\)

Multiply row two by\( - 1\).

\(\left( {\begin{aligned}{*{20}{c}}1&0&{ - 7}&2\\0&{ - 1}&{ - 4}&1\end{aligned}} \right) \sim \left( {\begin{aligned}{*{20}{c}}1&0&{ - 7}&2\\0&1&4&{ - 1}\end{aligned}} \right)\)

By comparing with\(\left( {\begin{aligned}{*{20}{c}}I&{{A^{ - 1}}}\end{aligned}} \right)\), you get\({A^{ - 1}} = \left( {\begin{aligned}{*{20}{c}}{ - 7}&2\\4&{ - 1}\end{aligned}} \right)\).

Thus, theinverse of the matrix is \(\left( {\begin{aligned}{*{20}{c}}{ - 7}&2\\4&{ - 1}\end{aligned}} \right)\).

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Most popular questions from this chapter

The inverse of \(\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\C&I&{\bf{0}}\\A&B&I\end{array}} \right]\) is \(\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\Z&I&{\bf{0}}\\X&Y&I\end{array}} \right]\). Find X, Y, and Z.

Show that \({I_n}A = A\) when \(A\) is \(m \times n\) matrix. (Hint: Use the (column) definition of \({I_n}A\).)

When a deep space probe launched, corrections may be necessary to place the probe on a precisely calculated trajectory. Radio elementary provides a stream of vectors, \({{\bf{x}}_{\bf{1}}},....,{{\bf{x}}_k}\), giving information at different times about how the probe’s position compares with its planned trajectory. Let \({X_k}\) be the matrix \(\left[ {{x_{\bf{1}}}.....{x_k}} \right]\). The matrix \({G_k} = {X_k}X_k^T\) is computed as the radar data are analyzed. When \({x_{k + {\bf{1}}}}\) arrives, a new \({G_{k + {\bf{1}}}}\) must be computed. Since the data vector arrive at high speed, the computational burden could be serve. But partitioned matrix multiplication helps tremendously. Compute the column-row expansions of \({G_k}\) and \({G_{k + {\bf{1}}}}\) and describe what must be computed in order to update \({G_k}\) to \({G_{k + {\bf{1}}}}\).

Assume \(A - s{I_n}\) is invertible and view (8) as a system of two matrix equations. Solve the top equation for \({\bf{x}}\) and substitute into the bottom equation. The result is an equation of the form \(W\left( s \right){\bf{u}} = {\bf{y}}\), where \(W\left( s \right)\) is a matrix that depends upon \(s\). \(W\left( s \right)\) is called the transfer function of the system because it transforms the input \({\bf{u}}\) into the output \({\bf{y}}\). Find \(W\left( s \right)\) and describe how it is related to the partitioned system matrix on the left side of (8). See Exercise 15.

Show that if ABis invertible, so is B.

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