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Question:In Exercises 15–18, find a basis for the space spanned by the given vectors,\({{\bf{v}}_{\bf{1}}}, \ldots ,{{\bf{v}}_{\bf{5}}}\).

15. \(\left[ {\begin{array}{*{20}{c}}1\\{\bf{0}}\\{ - {\bf{3}}}\\{\bf{2}}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{\bf{0}}\\{\bf{1}}\\{\bf{2}}\\{ - {\bf{3}}}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{ - {\bf{3}}}\\{ - {\bf{4}}}\\{\bf{1}}\\{\bf{6}}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{\bf{1}}\\{ - {\bf{3}}}\\{ - {\bf{8}}}\\7\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{\bf{2}}\\{\bf{1}}\\{ - {\bf{6}}}\\{\bf{9}}\end{array}} \right]\)

Short Answer

Expert verified

The basis for the space spanned by the vectors is \(\left\{ {\left[ {\begin{array}{*{20}{c}}1\\0\\{ - 3}\\2\end{array}} \right],\left[ {\begin{array}{*{20}{c}}0\\1\\2\\{ - 3}\end{array}} \right],\left[ {\begin{array}{*{20}{c}}1\\{ - 3}\\{ - 8}\\7\end{array}} \right]} \right\}\).

Step by step solution

01

State the basis for Col A

The set of all linear combinations of the columns of matrix A is Col A.It is called the column space of A. Pivot columns are the basis for Col A.

02

Obtain the row-reduced echelon form

Consider the vectors\(\left[ {\begin{array}{*{20}{c}}1\\0\\{ - 3}\\2\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}0\\1\\2\\{ - 3}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{ - 3}\\{ - 4}\\1\\6\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}1\\{ - 3}\\{ - 8}\\7\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}2\\1\\{ - 6}\\9\end{array}} \right]\).

Five vectors span the column spaceof a matrix. So, construct matrix A using the given vectors as shown below:

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

Obtain theechelon formof matrix A as shown below:

Add 3 times row 1 to row 3 to get row 3.

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

Add\( - 2\)times row 1 to row 4 to get row 4.

\(A = \left[ {\begin{array}{*{20}{c}}1&0&{ - 3}&1&2\\0&1&{ - 4}&{ - 3}&1\\0&2&{ - 8}&{ - 5}&0\\0&{ - 3}&{12}&5&5\end{array}} \right]\)

Add\( - 2\)times row 2 to row 3 to get row 3. Then, add 3 times row 2 to row 4 to get row 4.

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

Add\( - 1\)timesrow 3 to row 1 to get row 1. And add 3row3 to row 2 to get row 2. Then, add 4 times row 3 to row 4 to get row 4.

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

03

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.

\(A = \left[ {\begin{array}{*{20}{c}} {\boxed1}&0&{ - 3}&0&4 \\ 0&{\boxed1}&{ - 4}&0&{ - 5} \\ 0&0&0&{\boxed1}&{ - 2} \\ 0&0&0&0&0 \end{array}} \right]\)

The first, second, and fourth columns have pivot elements.

The corresponding columns of matrix A are shown below:

\(\left[ {\begin{array}{*{20}{c}}1\\0\\{ - 3}\\2\end{array}} \right]\),\(\left[ {\begin{array}{*{20}{c}}0\\1\\2\\{ - 3}\end{array}} \right]\),\(\left[ {\begin{array}{*{20}{c}}1\\{ - 3}\\{ - 8}\\7\end{array}} \right]\)

The column space is shown below:

\({\rm{Col }}A = \left\{ {\left[ {\begin{array}{*{20}{c}}1\\0\\{ - 3}\\2\end{array}} \right],\left[ {\begin{array}{*{20}{c}}0\\1\\2\\{ - 3}\end{array}} \right],\left[ {\begin{array}{*{20}{c}}1\\{ - 3}\\{ - 8}\\7\end{array}} \right]} \right\}\)

Thus, the basis for Col Ais \(\left\{ {\left[ {\begin{array}{*{20}{c}}1\\0\\{ - 3}\\2\end{array}} \right],\left[ {\begin{array}{*{20}{c}}0\\1\\2\\{ - 3}\end{array}} \right],\left[ {\begin{array}{*{20}{c}}1\\{ - 3}\\{ - 8}\\7\end{array}} \right]} \right\}\).

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Most popular questions from this chapter

Exercises 23-26 concern a vector space V, a basis \(B = \left\{ {{{\bf{b}}_{\bf{1}}},....,{{\bf{b}}_n}\,} \right\}\)and the coordinate mapping \({\bf{x}} \mapsto {\left( {\bf{x}} \right)_B}\).

Given vectors, \({u_{\bf{1}}}\),….,\({u_p}\) and w in V, show that w is a linear combination of \({u_{\bf{1}}}\),….,\({u_p}\) if and only if \({\left( w \right)_B}\) is a linear combination of vectors \({\left( {{{\bf{u}}_{\bf{1}}}} \right)_B}\),….,\({\left( {{{\bf{u}}_p}} \right)_B}\).

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

14. Show that if \(Q\) is an invertible, then \({\mathop{\rm rank}\nolimits} AQ = {\mathop{\rm rank}\nolimits} A\). (Hint: Use Exercise 13 to study \({\mathop{\rm rank}\nolimits} {\left( {AQ} \right)^T}\).)

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

15. Let \(A\) be an \(m \times n\) matrix, and let \(B\) be a \(n \times p\) matrix such that \(AB = 0\). Show that \({\mathop{\rm rank}\nolimits} A + {\mathop{\rm rank}\nolimits} B \le n\). (Hint: One of the four subspaces \({\mathop{\rm Nul}\nolimits} A\), \({\mathop{\rm Col}\nolimits} A,\,{\mathop{\rm Nul}\nolimits} B\), and \({\mathop{\rm Col}\nolimits} B\) is contained in one of the other three subspaces.)

Question 18: Suppose A is a \(4 \times 4\) matrix and B is a \(4 \times 2\) matrix, and let \({{\mathop{\rm u}\nolimits} _0},...,{{\mathop{\rm u}\nolimits} _3}\) represent a sequence of input vectors in \({\mathbb{R}^2}\).

  1. Set \({{\mathop{\rm x}\nolimits} _0} = 0\), compute \({{\mathop{\rm x}\nolimits} _1},...,{{\mathop{\rm x}\nolimits} _4}\) from equation (1), and write a formula for \({{\mathop{\rm x}\nolimits} _4}\) involving the controllability matrix \(M\) appearing in equation (2). (Note: The matrix \(M\) is constructed as a partitioned matrix. Its overall size here is \(4 \times 8\).)
  2. Suppose \(\left( {A,B} \right)\) is controllable and v is any vector in \({\mathbb{R}^4}\). Explain why there exists a control sequence \({{\mathop{\rm u}\nolimits} _0},...,{{\mathop{\rm u}\nolimits} _3}\) in \({\mathbb{R}^2}\) such that \({{\mathop{\rm x}\nolimits} _4} = {\mathop{\rm v}\nolimits} \).

Suppose the solutions of a homogeneous system of five linear equations in six unknowns are all multiples of one nonzero solution. Will the system necessarily have a solution for every possible choice of constants on the right sides of the equations? Explain.

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