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Question: In Exercises 13 and 14, assume that A is row equivalent to B. Find bases for NulA and Col A.

13. \(A = \left[ {\begin{array}{*{20}{c}}{ - 2}&4&{ - 2}&{ - 4}\\2&{ - 6}&{ - 3}&1\\{ - 3}&8&2&{ - 3}\end{array}} \right]\), \(B = \left[ {\begin{array}{*{20}{c}}1&0&6&5\\0&2&5&3\\0&0&0&0\end{array}} \right]\)

Short Answer

Expert verified

The basis for Col Ais \(\left\{ {\left[ {\begin{array}{*{20}{c}}{ - 2}\\2\\{ - 3}\end{array}} \right],\left[ {\begin{array}{*{20}{c}}4\\{ - 6}\\8\end{array}} \right]} \right\}\). The basis for NulAis \(\left\{ {\left[ {\begin{array}{*{20}{c}}{ - 6}\\{ - \frac{5}{2}}\\1\\0\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 5}\\{ - \frac{3}{2}}\\0\\1\end{array}} \right]} \right\}\).

Step by step solution

01

Basis for Nul A and Col A

The set of alllinear combinations of the columns of matrix A is Col A.It is called thecolumn space of A. Pivot columns are thebasis for Col A.

The set of allhomogeneous equationsolutions,\(A{\bf{x}} = 0\), is NulA.0It is called thenull spaceof A.

02

Write the basis for Col A

To identify the pivot and the pivot position, observe the leftmost column (nonzero column) of the matrix, that is, the pivot column. At the top of this column, 1 is the pivot.

B = \(\left[ {\begin{array}{*{20}{c}} {\boxed1}&0&6&5 \\ 0&{\boxed2}&5&3 \\ 0&0&0&0 \end{array}} \right]\)

Here, the first and second columns have pivot elements.

The corresponding columns of matrix A are shown below:

\(\left[ {\begin{array}{*{20}{c}}{ - 2}\\2\\{ - 3}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}4\\{ - 6}\\8\end{array}} \right]\)

The column space is shown below:

\({\rm{Col }}A = \left\{ {\left[ {\begin{array}{*{20}{c}}{ - 2}\\2\\{ - 3}\end{array}} \right],\left[ {\begin{array}{*{20}{c}}4\\{ - 6}\\8\end{array}} \right]} \right\}\)

Thus, the basis for Col Ais \(\left\{ {\left[ {\begin{array}{*{20}{c}}{ - 2}\\2\\{ - 3}\end{array}} \right],\left[ {\begin{array}{*{20}{c}}4\\{ - 6}\\8\end{array}} \right]} \right\}\).

03

Write the basis for Nul A

It is given that there are fourcolumns in the given matrix.That means there should be four entries in vector x.

Thus, the equation \(A{\bf{x}} = 0\) can be written as shown below:

\(\begin{array}{c}Ax = 0\\\left[ {\begin{array}{*{20}{c}}1&0&6&5\\0&2&5&3\\0&0&0&0\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}0\\0\\0\end{array}} \right]\end{array}\)

So, the system of equations is

\(\begin{array}{c}{x_1} + 6{x_3} + 5{x_4} = 0,\\2{x_2} + 5{x_3} + 3{x_4} = 0.\end{array}\)

From the above equations,\({x_1}\)and \({x_2}\) correspondto the pivot positions. So, \({x_1}\) and\({x_2}\) are the basic variables, and\({x_3}\)and\({x_4}\) are the free variables.

Let \({x_3} = a\), \({x_4} = b\).

Substitute the values\({x_3} = a\)and \({x_4} = b\) in the equation \({x_1} + 6{x_3} + 5{x_4} = 0\) to obtain the general solution.

\(\begin{array}{c}{x_1} + 6\left( a \right) + 5\left( b \right) = 0\\{x_1} = - 6a - 5b\end{array}\)

Substitute the value \({x_3} = a\) and \({x_4} = b\) in the equation \(2{x_2} + 5{x_3} + 3{x_4} = 0\) to obtain the general solution.

\(\begin{array}{c}2{x_2} + 5\left( a \right) + 3\left( b \right) = 0\\{x_2} = - \frac{5}{2}a - \frac{3}{2}b\end{array}\)

Obtain the vector in the parametric form using \({x_1} = - 6a - 5b\), \({x_2} = - \frac{5}{2}a - \frac{3}{2}b\), \({x_3} = a\), and \({x_4} = b\).

\(\begin{array}{c}\left[ {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{ - 6a - 5b}\\{ - \frac{5}{2}a - \frac{3}{2}b}\\a\\b\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{ - 6a}\\{ - \frac{5}{2}}\\a\\0\end{array}} \right] + \left[ {\begin{array}{*{20}{c}}{ - 5b}\\{ - \frac{3}{2}b}\\0\\b\end{array}} \right]\\ = a\left[ {\begin{array}{*{20}{c}}{ - 6}\\{ - \frac{5}{2}}\\1\\0\end{array}} \right] + b\left[ {\begin{array}{*{20}{c}}{ - 5}\\{ - \frac{3}{2}}\\0\\1\end{array}} \right]\\ = {x_3}\left[ {\begin{array}{*{20}{c}}{ - 6}\\{ - \frac{5}{2}}\\1\\0\end{array}} \right] + {x_4}\left[ {\begin{array}{*{20}{c}}{ - 5}\\{ - \frac{3}{2}}\\0\\1\end{array}} \right]\end{array}\)

The basis of Nul A is shown below:

\({\rm{Nul }}A = \left\{ {\left[ {\begin{array}{*{20}{c}}{ - 6}\\{ - \frac{5}{2}}\\1\\0\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 5}\\{ - \frac{3}{2}}\\0\\1\end{array}} \right]} \right\}\)

Thus, the basis for NulAis \(\left\{ {\left[ {\begin{array}{*{20}{c}}{ - 6}\\{ - \frac{5}{2}}\\1\\0\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 5}\\{ - \frac{3}{2}}\\0\\1\end{array}} \right]} \right\}\).

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Most popular questions from this chapter

In Exercise 2, find the vector x determined by the given coordinate vector \({\left( x \right)_{\rm B}}\) and the given basis \({\rm B}\).

2. \({\rm B} = \left\{ {\left( {\begin{array}{*{20}{c}}{\bf{4}}\\{\bf{5}}\end{array}} \right),\left( {\begin{array}{*{20}{c}}{\bf{6}}\\{\bf{7}}\end{array}} \right)} \right\},{\left( x \right)_{\rm B}} = \left( {\begin{array}{*{20}{c}}{\bf{8}}\\{ - {\bf{5}}}\end{array}} \right)\)

In Exercise 18, Ais an \(m \times n\) matrix. Mark each statement True or False. Justify each answer.

18. a. If B is any echelon form of A, then the pivot columns of B form a basis for the column space of A.

b. Row operations preserve the linear dependence relations among the rows of A.

c. The dimension of the null space of A is the number of columns of A that are not pivot columns.

d. The row space of \({A^T}\) is the same as the column space of A.

e. If A and B are row equivalent, then their row spaces are the same.

Prove theorem 3 as follows: Given an \(m \times n\) matrix A, an element in \({\mathop{\rm Col}\nolimits} A\) has the form \(Ax\) for some x in \({\mathbb{R}^n}\). Let \(Ax\) and \(A{\mathop{\rm w}\nolimits} \) represent any two vectors in \({\mathop{\rm Col}\nolimits} A\).

  1. Explain why the zero vector is in \({\mathop{\rm Col}\nolimits} A\).
  2. Show that the vector \(A{\mathop{\rm x}\nolimits} + A{\mathop{\rm w}\nolimits} \) is in \({\mathop{\rm Col}\nolimits} A\).
  3. Given a scalar \(c\), show that \(c\left( {A{\mathop{\rm x}\nolimits} } \right)\) is in \({\mathop{\rm Col}\nolimits} A\).

Question: Exercises 12-17 develop properties of rank that are sometimes needed in applications. Assume the matrix \(A\) is \(m \times n\).

17. A submatrix of a matrix A is any matrix that results from deleting some (or no) rows and/or columns of A. It can be shown that A has rank \(r\) if and only if A contains an invertible \(r \times r\) submatrix and no longer square submatrix is invertible. Demonstrate part of this statement by explaining (a) why an \(m \times n\) matrix A of rank \(r\) has an \(m \times r\) submatrix \({A_1}\) of rank \(r\), and (b) why \({A_1}\) has an invertible \(r \times r\) submatrix \({A_2}\).

The concept of rank plays an important role in the design of engineering control systems, such as the space shuttle system mentioned in this chapter鈥檚 introductory example. A state-space model of a control system includes a difference equation of the form

\({{\mathop{\rm x}\nolimits} _{k + 1}} = A{{\mathop{\rm x}\nolimits} _k} + B{{\mathop{\rm u}\nolimits} _k}\)for \(k = 0,1,....\) (1)

Where \(A\) is \(n \times n\), \(B\) is \(n \times m\), \(\left\{ {{{\mathop{\rm x}\nolimits} _k}} \right\}\) is a sequence of 鈥渟tate vectors鈥 in \({\mathbb{R}^n}\) that describe the state of the system at discrete times, and \(\left\{ {{{\mathop{\rm u}\nolimits} _k}} \right\}\) is a control, or input, sequence. The pair \(\left( {A,B} \right)\) is said to be controllable if

\({\mathop{\rm rank}\nolimits} \left( {\begin{array}{*{20}{c}}B&{AB}&{{A^2}B}& \cdots &{{A^{n - 1}}B}\end{array}} \right) = n\) (2)

The matrix that appears in (2) is called the controllability matrix for the system. If \(\left( {A,B} \right)\) is controllable, then the system can be controlled, or driven from the state 0 to any specified state \({\mathop{\rm v}\nolimits} \) (in \({\mathbb{R}^n}\)) in at most \(n\) steps, simply by choosing an appropriate control sequence in \({\mathbb{R}^m}\). This fact is illustrated in Exercise 18 for \(n = 4\) and \(m = 2\). For a further discussion of controllability, see this text鈥檚 website (Case study for Chapter 4).

Suppose \({{\bf{p}}_{\bf{1}}}\), \({{\bf{p}}_{\bf{2}}}\), \({{\bf{p}}_{\bf{3}}}\), and \({{\bf{p}}_{\bf{4}}}\) are specific polynomials that span a two-dimensional subspace H of \({P_{\bf{5}}}\). Describe how one can find a basis for H by examining the four polynomials and making almost no computations.

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