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Exercises 23-26 display a matrix A and echelon form of A. Find a basis for Col A and a basis for Nul A.

\[A = \left[ {\begin{array}{*{20}{c}}{ - {\bf{3}}}&{\bf{9}}&{ - {\bf{2}}}&{ - {\bf{7}}}\\{\bf{2}}&{ - {\bf{6}}}&{\bf{4}}&{\bf{8}}\\{\bf{3}}&{ - {\bf{9}}}&{ - {\bf{2}}}&{\bf{2}}\end{array}} \right] \sim \left[ {\begin{array}{*{20}{c}}{\bf{1}}&{ - {\bf{3}}}&{\bf{6}}&{\bf{9}}\\{\bf{0}}&{\bf{0}}&{\bf{4}}&{\bf{5}}\\{\bf{0}}&{\bf{0}}&{\bf{0}}&{\bf{0}}\end{array}} \right]\]

Short Answer

Expert verified

\(\left\{ {\left[ {\begin{array}{*{20}{c}}{ - 3}\\2\\3\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 2}\\4\\{ - 2}\end{array}} \right]} \right\}\), \(\left\{ {\left[ {\begin{array}{*{20}{c}}3\\1\\0\\0\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - \frac{3}{2}}\\0\\{ - \frac{5}{4}}\\1\end{array}} \right]} \right\}\)

Step by step solution

01

Identify the pivot column using the echelon form

From the echelon form, it can be observed that columns 1 and 3 are thepivot columns.

02

Find the basis of Col A

The basis of Col A is

\(\left[ {\begin{array}{*{20}{c}}{ - 3}\\2\\3\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{ - 2}\\4\\{ - 2}\end{array}} \right]\).

03

Find the basis of Nul A

Nul A is given by the equation \(Ax = 0\). Then,

\[\left[ {\begin{array}{*{20}{c}}1&{ - 3}&6&9\\0&0&4&5\\0&0&0&0\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right]\].

So, the equations are

\({x_1} - 3{x_2} + 6{x_3} + 9{x_4} = 0\),

\({x_3} + \frac{5}{4}{x_4} = 0\).

04

Simplify the equation Nul A

For the equations, \({x_3}\) and \({x_4}\) are the free variables.

\(\begin{array}{c}{x_1} = 3{x_2} - 6{x_3} - 9{x_4}\\ = 3{x_2} - 6\left( { - \frac{5}{4}{x_4}} \right) - 9{x_4}\\ = 3{x_2} - \frac{3}{2}{x_4}\end{array}\)

The solution set is obtained as shown below:

\(\begin{array}{c}\left[ {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{3{x_2} - \frac{3}{2}{x_4}}\\{{x_2}}\\{ - \frac{5}{4}{x_4}}\\{{x_4}}\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{3{x_2}}\\{{x_2}}\\0\\0\end{array}} \right] + \left[ {\begin{array}{*{20}{c}}{ - \frac{3}{2}{x_4}}\\0\\{ - \frac{5}{4}{x_4}}\\{{x_4}}\end{array}} \right]\\ = {x_2}\left[ {\begin{array}{*{20}{c}}3\\1\\0\\0\end{array}} \right] + {x_4}\left[ {\begin{array}{*{20}{c}}{ - \frac{3}{2}}\\0\\{ - \frac{5}{4}}\\1\end{array}} \right]\end{array}\)

So, the basis of Col A is \(\left\{ {\left[ {\begin{array}{*{20}{c}}{ - 3}\\2\\3\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 2}\\4\\{ - 2}\end{array}} \right]} \right\}\) and the basis of Nul A is \(\left\{ {\left[ {\begin{array}{*{20}{c}}3\\1\\0\\0\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - \frac{3}{2}}\\0\\{ - \frac{5}{4}}\\1\end{array}} \right]} \right\}\).

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Most popular questions from this chapter

In the rest of this exercise set and in those to follow, you should assume that each matrix expression is defined. That is, the sizes of the matrices (and vectors) involved match appropriately.

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

Suppose block matrix \(A\) on the left side of (7) is invertible and \({A_{{\bf{11}}}}\) is invertible. Show that the Schur component \(S\) of \({A_{{\bf{11}}}}\) is invertible. [Hint: The outside factors on the right side of (7) are always invertible. Verify this.] When \(A\) and \({A_{{\bf{11}}}}\) are invertible, (7) leads to a formula for \({A^{ - {\bf{1}}}}\), using \({S^{ - {\bf{1}}}}\) \(A_{{\bf{11}}}^{ - {\bf{1}}}\), and the other entries in \(A\).

Use matrix algebra to show that if A is invertible and D satisfies \(AD = I\) then \(D = {A^{ - {\bf{1}}}}\).

Exercises 15 and 16 concern arbitrary matrices A, B, and Cfor which the indicated sums and products are defined. Mark each statement True or False. Justify each answer.

15. a. If A and B are \({\bf{2}} \times {\bf{2}}\) with columns \({{\bf{a}}_1},{{\bf{a}}_2}\) and \({{\bf{b}}_1},{{\bf{b}}_2}\) respectively, then \(AB = \left( {\begin{aligned}{*{20}{c}}{{{\bf{a}}_1}{{\bf{b}}_1}}&{{{\bf{a}}_2}{{\bf{b}}_2}}\end{aligned}} \right)\).

b. Each column of ABis a linear combination of the columns of Busing weights from the corresponding column of A.

c. \(AB + AC = A\left( {B + C} \right)\)

d. \({A^T} + {B^T} = {\left( {A + B} \right)^T}\)

e. The transpose of a product of matrices equals the product of their transposes in the same order.

Suppose Ais an \(n \times n\) matrix with the property that the equation \[A{\mathop{\rm x}\nolimits} = 0\] has at least one solution for each b in \({\mathbb{R}^n}\). Without using Theorem 5 or 8, explain why each equation Ax = b has in fact exactly one solution.

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