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Let \(A = \left\{ {{{\mathop{\rm a}\nolimits} _1},{{\mathop{\rm a}\nolimits} _2},{{\mathop{\rm a}\nolimits} _3}} \right\}\) and \(B = \left\{ {{{\mathop{\rm b}\nolimits} _1},{{\mathop{\rm b}\nolimits} _2},{{\mathop{\rm b}\nolimits} _3}} \right\}\) be bases for a vector space \(V\), and suppose \({{\mathop{\rm a}\nolimits} _1} = 4{b_1} - {b_2}\), \({{\mathop{\rm a}\nolimits} _2} = - {b_1} + {b_2} + {{\mathop{\rm b}\nolimits} _3}\) and \({{\mathop{\rm a}\nolimits} _3} = {b_2} - 2{{\mathop{\rm b}\nolimits} _3}\).

a. Find the change-of-coordinates matrix from \(A\) to \(B\).

b. Find \({\left[ {\mathop{\rm x}\nolimits} \right]_B}\) for \({\mathop{\rm x}\nolimits} = 3{{\mathop{\rm a}\nolimits} _1} + 4{{\mathop{\rm a}\nolimits} _2} + {{\mathop{\rm a}\nolimits} _3}\).

Short Answer

Expert verified
  1. The change-of-coordinates matrix from \(A\) to \(B\) is \(\mathop P\limits_{B \leftarrow A} = \left[ {\begin{array}{*{20}{c}}4&{ - 1}&0\\{ - 1}&1&1\\0&1&{ - 2}\end{array}} \right]\).
  2. The \(B - \)coordinate vector is \({\left[ {\mathop{\rm x}\nolimits} \right]_B} = \left[ {\begin{array}{*{20}{c}}8\\2\\2\end{array}} \right]\).

Step by step solution

01

State the change-of-coordinate matrix

Let \(B = \left\{ {{{\mathop{\rm b}\nolimits} _1},...,{{\mathop{\rm b}\nolimits} _n}} \right\}\) and \(C = \left\{ {{{\mathop{\rm c}\nolimits} _1},...,{{\mathop{\rm c}\nolimits} _n}} \right\}\) be bases of a vector space \(V\). Then according to Theorem 15,there is a unique \(n \times n\) matrix \(\mathop P\limits_{C \leftarrow B} \) such that \({\left[ {\mathop{\rm x}\nolimits} \right]_C} = \mathop P\limits_{C \leftarrow B} {\left[ {\mathop{\rm x}\nolimits} \right]_B}\).

The columns of \(\mathop P\limits_{C \leftarrow B} \) are the \(C - \)coordinate vectors of the vectors in the basis \(B\). That is, \(\mathop P\limits_{C \leftarrow B} = \left[ {\begin{array}{*{20}{c}}{{{\left[ {{{\mathop{\rm b}\nolimits} _1}} \right]}_C}}&{{{\left[ {{{\mathop{\rm b}\nolimits} _2}} \right]}_C}}& \cdots &{{{\left[ {{{\mathop{\rm b}\nolimits} _n}} \right]}_C}}\end{array}} \right]\).

02

Determine the change-of-coordinate matrix from \(A\) to \(B\)

a)

It is given that \({{\mathop{\rm a}\nolimits} _1} = 4{{\mathop{\rm b}\nolimits} _1} - {{\mathop{\rm b}\nolimits} _2},{{\mathop{\rm a}\nolimits} _2} = - {{\mathop{\rm b}\nolimits} _1} + {{\mathop{\rm b}\nolimits} _2} + {{\mathop{\rm b}\nolimits} _3},\) and \({{\mathop{\rm a}\nolimits} _3} = {{\mathop{\rm b}\nolimits} _2} - 2{{\mathop{\rm b}\nolimits} _3}\). Then, \({\left[ {{{\mathop{\rm a}\nolimits} _1}} \right]_B} = \left[ {\begin{array}{*{20}{c}}4\\{ - 1}\\0\end{array}} \right],{\left[ {{{\mathop{\rm a}\nolimits} _2}} \right]_B} = \left[ {\begin{array}{*{20}{c}}{ - 1}\\1\\1\end{array}} \right],{\left[ {{{\mathop{\rm a}\nolimits} _3}} \right]_B} = \left[ {\begin{array}{*{20}{c}}0\\1\\{ - 2}\end{array}} \right]\).

\(\begin{aligned} \mathop P\limits_{B \leftarrow A} &= \left[ {\begin{array}{*{20}{c}}{{{\left[ {{{\mathop{\rm a}\nolimits} _1}} \right]}_B}}&{{{\left[ {{{\mathop{\rm a}\nolimits} _2}} \right]}_B}}&{{{\left[ {{{\mathop{\rm a}\nolimits} _3}} \right]}_B}}\end{array}} \right]\\ &= \left[ {\begin{array}{*{20}{c}}4&{ - 1}&0\\{ - 1}&1&1\\0&1&{ - 2}\end{array}} \right]\end{aligned}\)

Thus, the change-of-coordinates matrix from \(A\) to \(B\) is \(\mathop P\limits_{B \leftarrow A} = \left[ {\begin{array}{*{20}{c}}4&{ - 1}&0\\{ - 1}&1&1\\0&1&{ - 2}\end{array}} \right]\).

03

Determine \({\left[ {\mathop{\rm x}\nolimits}   \right]_B}\) for \({\mathop{\rm x}\nolimits}  = 3{{\mathop{\rm a}\nolimits} _1} + 4{{\mathop{\rm a}\nolimits} _2} + {{\mathop{\rm a}\nolimits} _3}\)

b)

It is given that \({\mathop{\rm x}\nolimits} = 3{{\mathop{\rm a}\nolimits} _1} + 4{{\mathop{\rm a}\nolimits} _2} + {{\mathop{\rm a}\nolimits} _3}\), then \({\left[ {\mathop{\rm x}\nolimits} \right]_A} = \left[ {\begin{array}{*{20}{c}}3\\4\\1\end{array}} \right]\).

Use part (a) to compute the B-coordinate vector.

\(\begin{aligned} {\left[ {\mathop{\rm x}\nolimits} \right]_B} &= \mathop P\limits_{B \leftarrow A} {\left[ {\mathop{\rm x}\nolimits} \right]_A}\\ &= \left[ {\begin{array}{*{20}{c}}4&{ - 1}&0\\{ - 1}&1&1\\0&1&{ - 2}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}3\\4\\1\end{array}} \right]\\ &= \left[ {\begin{array}{*{20}{c}}{12 - 4 + 0}\\{ - 3 + 5 + 1}\\{0 + 4 - 2}\end{array}} \right]\\ &= \left[ {\begin{array}{*{20}{c}}8\\2\\2\end{array}} \right]\end{aligned}\)

Therefore, the \(B - \)coordinate vector is \({\left[ {\mathop{\rm x}\nolimits} \right]_B} = \left[ {\begin{array}{*{20}{c}}8\\2\\2\end{array}} \right]\).

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Most popular questions from this chapter

Given \(T:V \to W\) as in Exercise 35, and given a subspace \(Z\) of \(W\), let \(U\) be the set of all \({\mathop{\rm x}\nolimits} \) in \(V\) such that \(T\left( {\mathop{\rm x}\nolimits} \right)\) is in \(Z\). Show that \(U\) is a subspace of \(V\).

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

  1. Show that if \(B\) is \(n \times p\), then rank\(AB \le {\mathop{\rm rank}\nolimits} A\). (Hint: Explain why every vector in the column space of \(AB\) is in the column space of \(A\).
  2. Show that if \(B\) is \(n \times p\), then rank\(AB \le {\mathop{\rm rank}\nolimits} B\). (Hint: Use part (a) to study rank\({\left( {AB} \right)^T}\).)

Let \(T:{\mathbb{R}^n} \to {\mathbb{R}^m}\) be a linear transformation.

a. What is the dimension of range of T if T is one-to-one mapping? Explain.

b. What is the dimension of the kernel of T (see section 4.2) if T maps \({\mathbb{R}^n}\) onto \({\mathbb{R}^m}\)? Explain.

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

  1. Construct matrices \(C\) and \(N\) whose columns are bases for \({\mathop{\rm Col}\nolimits} A\) and \({\mathop{\rm Nul}\nolimits} A\), respectively, and construct a matrix \(R\) whose rows form a basis for Row\(A\).
  2. Construct a matrix \(M\) whose columns form a basis for \({\mathop{\rm Nul}\nolimits} {A^T}\), form the matrices \(S = \left[ {\begin{array}{*{20}{c}}{{R^T}}&N\end{array}} \right]\) and \(T = \left[ {\begin{array}{*{20}{c}}C&M\end{array}} \right]\), and explain why \(S\) and \(T\) should be square. Verify that both \(S\) and \(T\) are invertible.

Let be a basis of\({\mathbb{R}^n}\). .Produce a description of an \(B = \left\{ {{{\bf{b}}_{\bf{1}}},....,{{\bf{b}}_n}\,} \right\}\)matrix A that implements the coordinate mapping \({\bf{x}} \mapsto {\left( {\bf{x}} \right)_B}\). Find it. (Hint: Multiplication by A should transform a vector x into its coordinate vector \({\left( {\bf{x}} \right)_B}\)). (See Exercise 21.)

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