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Let \({v_1} = \left( {\begin{array}{*{20}{c}}4\\{ - 3}\\7\end{array}} \right)\), \({v_2} = \left( {\begin{array}{*{20}{c}}1\\9\\{ - 2}\end{array}} \right)\), \({v_3} = \left( {\begin{array}{*{20}{c}}7\\{11}\\6\end{array}} \right)\), and \(H = Span\left\{ {{v_1},{v_2},{v_3}} \right\}\). It can be verified that \(4{v_1} + 5{v_2} - 3{v_3} = 0\). Use this information to find a basis for \(H\). There is more than one answer

Short Answer

Expert verified

Each vector forms a basis for H.

Step by step solution

01

State the condition for span and linear independence

Vector \({{\bf{v}}_3}\) is said to be in the Span \(\left\{ {{{\bf{v}}_1},{{\bf{v}}_2}} \right\}\) if the equation \({x_1}{{\bf{v}}_1} + {x_2}{{\bf{v}}_2} = {{\bf{v}}_3}\) has a solution, where \({{\bf{v}}_1}\), \({{\bf{v}}_2}\), and \({{\bf{v}}_3}\) are vectors.

The vectors are said to be linearly independent if the equation \({x_1}{{\bf{v}}_1} + {x_2}{{\bf{v}}_2} + {x_3}{{\bf{v}}_3} + ... + {x_p}{{\bf{v}}_p} = 0\) has a trivial solution, where \({{\bf{v}}_1},{{\bf{v}}_2},...,{{\bf{v}}_p}\) are vectors.

02

Verify the condition

Consider the vectors\({{\bf{v}}_1} = \left( {\begin{array}{*{20}{c}}4\\{ - 3}\\7\end{array}} \right)\), \({{\bf{v}}_2} = \left( {\begin{array}{*{20}{c}}1\\9\\{ - 2}\end{array}} \right)\), \({{\bf{v}}_3} = \left( {\begin{array}{*{20}{c}}7\\{11}\\6\end{array}} \right)\).

Substitute the above vectors in the equation\(4{{\bf{v}}_1} + 5{{\bf{v}}_2} - 3{{\bf{v}}_3} = 0\).

\(\begin{array}{c}4\left( {\begin{array}{*{20}{c}}4\\{ - 3}\\7\end{array}} \right) + 5\left( {\begin{array}{*{20}{c}}1\\9\\{ - 2}\end{array}} \right) - 3\left( {\begin{array}{*{20}{c}}7\\{11}\\6\end{array}} \right) = 0\\\left( {\begin{array}{*{20}{c}}{16}\\{ - 12}\\{28}\end{array}} \right) + \left( {\begin{array}{*{20}{c}}5\\{45}\\{ - 10}\end{array}} \right) - \left( {\begin{array}{*{20}{c}}{21}\\{33}\\{18}\end{array}} \right) = 0\\\left( {\begin{array}{*{20}{c}}{15 + 5 - 21}\\{ - 12 + 45 - 33}\\{28 - 10 - 18}\end{array}} \right) = 0\\0 = 0\end{array}\)

Hence, the relation\(4{{\bf{v}}_1} + 5{{\bf{v}}_2} - 3{{\bf{v}}_3} = 0\)is verified.

03

Rearrange the vectors

Take the equation\(4{{\bf{v}}_1} + 5{{\bf{v}}_2} - 3{{\bf{v}}_3} = 0\), and write vector\({{\bf{v}}_1}\)in terms of the other two vectors,\({{\bf{v}}_2}\)and\({{\bf{v}}_3}\), as shown below:

\({{\bf{v}}_1} = - \frac{5}{4}{{\bf{v}}_2} + \frac{3}{4}{{\bf{v}}_3}\)

Take the equation\(4{{\bf{v}}_1} + 5{{\bf{v}}_2} - 3{{\bf{v}}_3} = 0\), and write vector\({{\bf{v}}_2}\)in terms of the other two vectors,\({{\bf{v}}_1}\)and\({{\bf{v}}_3}\), as shown below:

\({{\bf{v}}_2} = - \frac{4}{5}{{\bf{v}}_1} + \frac{3}{5}{{\bf{v}}_3}\)

Take the equation\(4{{\bf{v}}_1} + 5{{\bf{v}}_2} - 3{{\bf{v}}_3} = 0\), and write vector\({{\bf{v}}_3}\)in terms of the other two vectors,\({{\bf{v}}_1}\)and\({{\bf{v}}_2}\), as shown below:

\({{\bf{v}}_3} = \frac{4}{3}{{\bf{v}}_1} + \frac{5}{3}{{\bf{v}}_2}\)

Thus, all vectors are linear combinations of each other.

04

Obtain the basis for H

From the equation\({{\bf{v}}_1} = - \frac{5}{4}{{\bf{v}}_2} + \frac{3}{4}{{\bf{v}}_3}\), the set\(\left\{ {{{\bf{v}}_2},{{\bf{v}}_3}} \right\}\)span H.

From the equation\({{\bf{v}}_2} = - \frac{4}{5}{{\bf{v}}_1} + \frac{3}{5}{{\bf{v}}_3}\), the set\(\left\{ {{{\bf{v}}_1},{{\bf{v}}_3}} \right\}\)span H.

From the equation\({{\bf{v}}_3} = \frac{4}{3}{{\bf{v}}_1} + \frac{5}{3}{{\bf{v}}_2}\), the set\(\left\{ {{{\bf{v}}_1},{{\bf{v}}_2}} \right\}\)span H.

Also, no vector is a multiple of another vector.

Thus, the sets\(\left\{ {{{\bf{v}}_2},{{\bf{v}}_3}} \right\}\),\(\left\{ {{{\bf{v}}_1},{{\bf{v}}_3}} \right\}\), and\(\left\{ {{{\bf{v}}_1},{{\bf{v}}_2}} \right\}\)are linearly independent and they all form a basis for H.

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Most popular questions from this chapter

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.

Let \({M_{2 \times 2}}\) be the vector space of all \(2 \times 2\) matrices, and define \(T:{M_{2 \times 2}} \to {M_{2 \times 2}}\) by \(T\left( A \right) = A + {A^T}\), where \(A = \left( {\begin{array}{*{20}{c}}a&b\\c&d\end{array}} \right)\).

  1. Show that \(T\)is a linear transformation.
  2. Let \(B\) be any element of \({M_{2 \times 2}}\) such that \({B^T} = B\). Find an \(A\) in \({M_{2 \times 2}}\) such that \(T\left( A \right) = B\).
  3. Show that the range of \(T\) is the set of \(B\) in \({M_{2 \times 2}}\) with the property that \({B^T} = B\).
  4. Describe the kernel of \(T\).

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 \({\mathop{\rm rank}\nolimits} {\left( {AQ} \right)^T}\).)

If a\({\bf{6}} \times {\bf{3}}\)matrix A has a rank 3, find dim Nul A, dim Row A, and rank\({A^T}\).

Let be a linear transformation from a vector space \(V\) \(T:V \to W\)in to vector space \(W\). Prove that the range of T is a subspace of . (Hint: Typical elements of the range have the form \(T\left( {\mathop{\rm x}\nolimits} \right)\) and \(T\left( {\mathop{\rm w}\nolimits} \right)\) for some \({\mathop{\rm x}\nolimits} ,\,{\mathop{\rm w}\nolimits} \)in \(V\).)\(W\)

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