Let \(A = \left( {\begin{aligned}{*{20}{c}}{\bf{1}}&{\bf{2}}\\{\bf{5}}&{{\bf{12}}}\end{aligned}} \right),{b_{\bf{1}}} = \left( {\begin{aligned}{*{20}{c}}{ - {\bf{1}}}\\{\bf{3}}\end{aligned}} \right),{b_{\bf{2}}} = \left( {\begin{aligned}{*{20}{c}}{\bf{1}}\\{ - {\bf{5}}}\end{aligned}} \right),{b_{\bf{3}}} = \left( {\begin{aligned}{*{20}{c}}{\bf{2}}\\{\bf{6}}\end{aligned}} \right),\) and \({b_{\bf{4}}} = \left( {\begin{aligned}{*{20}{c}}{\bf{3}}\\{\bf{5}}\end{aligned}} \right)\).

  1. Find \({A^{ - {\bf{1}}}}\), and use it to solve the four equations \(Ax = {b_{\bf{1}}},\)\(Ax = {b_2},\)\(Ax = {b_{\bf{3}}},\)\(Ax = {b_{\bf{4}}}\)\(\)
  2. The four equations in part (a) can be solved by the same set of row operations, since the coefficient matrix is the same in each case. Solve the four equations in part (a) by row reducing the augmented matrix \(\left( {\begin{aligned}{*{20}{c}}A&{{b_{\bf{1}}}}&{{b_{\bf{2}}}}&{{b_{\bf{3}}}}&{{b_{\bf{4}}}}\end{aligned}} \right)\).

Short Answer

Expert verified
  1. \({A^{ - 1}} = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12}&{ - 2}\\{ - 5}&1\end{aligned}} \right)\), and the solutions of the equations are \({A^{ - 1}}{b_1} = \left( {\begin{aligned}{*{20}{c}}{ - 9}\\4\end{aligned}} \right),\)\({A^{ - 1}}{b_2} = \left( {\begin{aligned}{*{20}{c}}{11}\\{ - 5}\end{aligned}} \right),\)\({A^{ - 1}}{b_3} = \left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\end{aligned}} \right),\) and \({A^{ - 1}}{b_4} = \left( {\begin{aligned}{*{20}{c}}{13}\\{ - 5}\end{aligned}} \right)\).
  2. The solutions are \(\left( {\begin{aligned}{*{20}{c}}{ - 9}\\4\end{aligned}} \right),\left( {\begin{aligned}{*{20}{c}}{11}\\{ - 5}\end{aligned}} \right),\left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\end{aligned}} \right),\) and \(\left( {\begin{aligned}{*{20}{c}}{13}\\{ - 5}\end{aligned}} \right)\), same as in part (a).

Step by step solution

01

Check if A is invertible

\(\begin{aligned}{c}\det A = 1\left( {12} \right) - 2\left( 5 \right)\\ = 12 - 10\\\det A = 2 \ne 0\end{aligned}\)

This implies that A is invertible.

02

Write the inverse of A

(a)

\({A^{ - 1}} = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12}&{ - 2}\\{ - 5}&1\end{aligned}} \right)\)

03

Find the solutions using \({A^{ - {\bf{1}}}}\)

The solution for the system \(Ax = {b_1}\) is obtained as shown below:

\(\begin{aligned}{c}x = {A^{ - 1}}{b_1}\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12}&{ - 2}\\{ - 5}&1\end{aligned}} \right)\left( {\begin{aligned}{*{20}{c}}{ - 1}\\3\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{ - 12 - 6}\\{5 + 3}\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{ - 18}\\8\end{aligned}} \right)\\x = \left( {\begin{aligned}{*{20}{c}}{ - 9}\\4\end{aligned}} \right)\end{aligned}\)

The solution for the system \(Ax = {b_2}\) is obtained as shown below:

\(\begin{aligned}{c}x = {A^{ - 1}}{b_2}\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12}&{ - 2}\\{ - 5}&1\end{aligned}} \right)\left( {\begin{aligned}{*{20}{c}}1\\{ - 5}\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12 + 10}\\{ - 5 - 5}\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{22}\\{ - 10}\end{aligned}} \right)\\x = \left( {\begin{aligned}{*{20}{c}}{11}\\{ - 5}\end{aligned}} \right)\end{aligned}\)

The solution for the system \(Ax = {b_3}\) is obtained as shown below:

\(\begin{aligned}{c}x = {A^{ - 1}}{b_3}\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12}&{ - 2}\\{ - 5}&1\end{aligned}} \right)\left( {\begin{aligned}{*{20}{c}}2\\6\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{24 - 12}\\{ - 10 + 6}\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12}\\{ - 4}\end{aligned}} \right)\\x = \left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\end{aligned}} \right)\end{aligned}\)

The solution for the system \(Ax = {b_4}\) is obtained as shown below:

\(\begin{aligned}{c}x = {A^{ - 1}}{b_4}\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{12}&{ - 2}\\{ - 5}&1\end{aligned}} \right)\left( {\begin{aligned}{*{20}{c}}3\\5\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{36 - 10}\\{ - 15 + 5}\end{aligned}} \right)\\ = \frac{1}{2}\left( {\begin{aligned}{*{20}{c}}{26}\\{ - 10}\end{aligned}} \right)\\x = \left( {\begin{aligned}{*{20}{c}}{13}\\{ - 5}\end{aligned}} \right)\end{aligned}\)

04

Reduce the augmented matrix \(\left(

{\begin{aligned}{*{20}{c}}A&{{b_{\bf{1}}}}&{{b_{\bf{2}}}}&{{b_{\bf{3}}}}&{{b_{\bf{4}}}}\end{aligned}} \right)\)

(b)

\(\left( {\begin{aligned}{*{20}{c}}A&{{b_1}}&{{b_2}}&{{b_2}}&{{b_4}}\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}1&2&{ - 1}&1&2&3\\5&{12}&3&{ - 5}&6&5\end{aligned}} \right)\)

At row two, multiply row one by 5 and subtract it from row two, i.e., \({R_2} \to {R_2} - 5{R_1}\).

\( \sim \left( {\begin{aligned}{*{20}{c}}1&2&{ - 1}&1&2&3\\0&2&8&{ - 10}&{ - 4}&{ - 10}\end{aligned}} \right)\)

Divide row two by 2.

\( \sim \left( {\begin{aligned}{*{20}{c}}1&2&{ - 1}&1&2&3\\0&1&4&{ - 5}&{ - 2}&{ - 5}\end{aligned}} \right)\)

At row one, multiply row two by 2 and subtract it from row one, i.e., \({R_1} \to {R_1} - 2{R_2}\).

\( \sim \left( {\begin{aligned}{*{20}{c}}1&0&{ - 9}&{11}&6&{13}\\0&1&4&{ - 5}&{ - 2}&{ - 5}\end{aligned}} \right)\)

This implies that the solutions are \(\left( {\begin{aligned}{*{20}{c}}{ - 9}\\4\end{aligned}} \right),\left( {\begin{aligned}{*{20}{c}}{11}\\{ - 5}\end{aligned}} \right),\left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\end{aligned}} \right),\) and \(\left( {\begin{aligned}{*{20}{c}}{13}\\{ - 5}\end{aligned}} \right)\), same as in part (a).

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Most popular questions from this chapter

Let \(X\) be \(m \times n\) data matrix such that \({X^T}X\) is invertible., and let \(M = {I_m} - X{\left( {{X^T}X} \right)^{ - {\bf{1}}}}{X^T}\). Add a column \({x_{\bf{0}}}\) to the data and form

\(W = \left[ {\begin{array}{*{20}{c}}X&{{x_{\bf{0}}}}\end{array}} \right]\)

Compute \({W^T}W\). The \(\left( {{\bf{1}},{\bf{1}}} \right)\) entry is \({X^T}X\). Show that the Schur complement (Exercise 15) of \({X^T}X\) can be written in the form \({\bf{x}}_{\bf{0}}^TM{{\bf{x}}_{\bf{0}}}\). It can be shown that the quantity \({\left( {{\bf{x}}_{\bf{0}}^TM{{\bf{x}}_{\bf{0}}}} \right)^{ - {\bf{1}}}}\) is the \(\left( {{\bf{2}},{\bf{2}}} \right)\)-entry in \({\left( {{W^T}W} \right)^{ - {\bf{1}}}}\). This entry has a useful statistical interpretation, under appropriate hypotheses.

In the study of engineering control of physical systems, a standard set of differential equations is transformed by Laplace transforms into the following system of linear equations:

\(\left[ {\begin{array}{*{20}{c}}{A - s{I_n}}&B\\C&{{I_m}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{\bf{x}}\\{\bf{u}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{\bf{0}}\\{\bf{y}}\end{array}} \right]\)

Where \(A\) is \(n \times n\), \(B\) is \(n \times m\), \(C\) is \(m \times n\), and \(s\) is a variable. The vector \({\bf{u}}\) in \({\mathbb{R}^m}\) is the “input” to the system, \({\bf{y}}\) in \({\mathbb{R}^m}\) is the “output” and \({\bf{x}}\) in \({\mathbb{R}^n}\) is the “state” vector. (Actually, the vectors \({\bf{x}}\), \({\bf{u}}\) and \({\bf{v}}\) are functions of \(s\), but we suppress this fact because it does not affect the algebraic calculations in Exercises 19 and 20.)

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.

In exercise 11 and 12, mark each statement True or False.Justify each answer.

a. If \(A = \left[ {\begin{array}{*{20}{c}}{{A_{\bf{1}}}}&{{A_{\bf{2}}}}\end{array}} \right]\) and \(B = \left[ {\begin{array}{*{20}{c}}{{B_{\bf{1}}}}&{{B_{\bf{2}}}}\end{array}} \right]\), with \({A_{\bf{1}}}\) and \({A_{\bf{2}}}\) the same sizes as \({B_{\bf{1}}}\) and \({B_{\bf{2}}}\), respectively then \(A + B = \left[ {\begin{array}{*{20}{c}}{{A_1} + {B_1}}&{{A_{\bf{2}}} + {B_{\bf{2}}}}\end{array}} \right]\).

b. If \(A = \left[ {\begin{array}{*{20}{c}}{{A_{{\bf{11}}}}}&{{A_{{\bf{12}}}}}\\{{A_{{\bf{21}}}}}&{{A_{{\bf{22}}}}}\end{array}} \right]\) and \(B = \left[ {\begin{array}{*{20}{c}}{{B_1}}\\{{B_{\bf{2}}}}\end{array}} \right]\), then the partitions of \(A\) and \(B\) are comfortable for block multiplication.

Let \({{\bf{r}}_1} \ldots ,{{\bf{r}}_p}\) be vectors in \({\mathbb{R}^{\bf{n}}}\), and let Qbe an\(m \times n\)matrix. Write the matrix\(\left( {\begin{aligned}{*{20}{c}}{Q{{\bf{r}}_1}}& \cdots &{Q{{\bf{r}}_p}}\end{aligned}} \right)\)as a productof two matrices (neither of which is an identity matrix).

Suppose a linear transformation \(T:{\mathbb{R}^n} \to {\mathbb{R}^n}\) has the property that \(T\left( {\mathop{\rm u}\nolimits} \right) = T\left( {\mathop{\rm v}\nolimits} \right)\) for some pair of distinct vectors u and v in \({\mathbb{R}^n}\). Can Tmap \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\)? Why or why not?

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