Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

Find the \(B\) matrix for the transformation\({\rm{x}} \mapsto A{\rm{x}}\), when \(B = \left\{ {{b_1},{b_2},{b_3}} \right\}\).

\(A = \left( {\begin{aligned}{}{ - 7}&{ - 48}&{ - 16}\\1&{14}&6\\{ - 3}&{ - 45}&{ - 19}\end{aligned}} \right)\),

\({b_1} = \left( {\begin{aligned}{}{ - 3}\\1\\{ - 3}\end{aligned}} \right)\), \({b_2} = \left( {\begin{aligned}{}{ - 2}\\1\\{ - 3}\end{aligned}} \right)\), \({b_3} = \left( {\begin{aligned}{}{\,\,\,3}\\{ - 1}\\{\,\,\,0}\end{aligned}} \right)\)

Short Answer

Expert verified

The B matrix of the transformation \({\rm{x}} \mapsto A{\rm{x}}\)is \(D = {P^{ - 1}}AP\), which is \(\left( {\begin{aligned}{}{ - 7}&{}&{ - 2}&{}&{ - 6}\\0&{}&{ - 4}&{}&{ - 6}\\0&{}&0&{}&{ - 1}\end{aligned}} \right)\)

Step by step solution

01

Find P matrix

Let \(P\) is an invertible matrix and \(D\) is the diagonal matrix, such that the matrix A can be written as follows:

\(A = PD{P^{ - 1}}\)

Where the columns of the \(P\) matrix are the same as that of basis \(B\). So, the matrix \(P\) can be written as:

\(\begin{aligned}{c}P &= \left( {{{\rm{b}}_1}\,\,{{\rm{b}}_2}\,\,{{\rm{b}}_3}} \right)\\ &= \left( {\begin{aligned}{}{ - 3}&{}&{ - 2}&{}&3\\1&{}&1&{}&{ - 1}\\{ - 3}&{}&{ - 3}&{}&0\end{aligned}} \right)\end{aligned}\)

02

Find D matrix

As \(A = PD{P^{ - 1}}\) then the diagonal matrix \(D\) can be obtained as \(D = {P^{ - 1}}AP\). To find \(D = {P^{ - 1}}AP\), first, find \({P^{ - 1}}\)using the cofactors and determinant method.

\(\begin{aligned}{c}P &= \left( {\begin{aligned}{}{ - 3}&{}&{ - 2}&{}&3\\1&{}&1&{}&{ - 1}\\{ - 3}&{}&{ - 3}&{}&0\end{aligned}} \right)\\{P^{ - 1}} &= \left( {\begin{aligned}{}{ - 1}&{}&{ - 3}&{}&{ - 1/3}\\{\,\,1}&{}&{\,\,3}&{}&{\,0}\\{\,\,0}&{}&{ - 1}&{}&{ - 1/3}\end{aligned}} \right)\end{aligned}\)

Now find the matrix \(D\) as follows:

\(\begin{aligned}{c}D &= {P^{ - 1}}AP\\ &= \left( {\begin{aligned}{}{ - 1}&{}&{ - 3}&{}&{ - 1/3}\\{\,\,1}&{}&{\,\,3}&{}&{\,0}\\{\,\,0}&{}&{ - 1}&{}&{ - 1/3}\end{aligned}} \right)\left( {\begin{aligned}{}{ - 7}&{}&{ - 48}&{}&{ - 16}\\1&{}&{14}&{}&6\\{ - 3}&{}&{ - 45}&{}&{ - 19}\end{aligned}} \right)\left( {\begin{aligned}{}{ - 3}&{}&{ - 2}&{}&3\\1&{}&1&{}&{ - 1}\\{ - 3}&{}&{ - 3}&{}&0\end{aligned}} \right)\\ &= \left( {\begin{aligned}{}{ - 7}&{}&{ - 2}&{}&{ - 6}\\0&{}&{ - 4}&{}&{ - 6}\\0&{}&0&{}&{ - 1}\end{aligned}} \right)\end{aligned}\)

The B matrix of the transformation \({\rm{x}} \mapsto A{\rm{x}}\) is \(D = {P^{ - 1}}AP\), which is \(\left( {\begin{aligned}{}{ - 7}&{}&{ - 2}&{}&{ - 6}\\0&{}&{ - 4}&{}&{ - 6}\\0&{}&0&{}&{ - 1}\end{aligned}} \right)\).

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Exercises 19–23 concern the polynomial \(p\left( t \right) = {a_{\bf{0}}} + {a_{\bf{1}}}t + ... + {a_{n - {\bf{1}}}}{t^{n - {\bf{1}}}} + {t^n}\) and \(n \times n\) matrix \({C_p}\) called the companion matrix of \(p\): \({C_p} = \left( {\begin{aligned}{*{20}{c}}{\bf{0}}&{\bf{1}}&{\bf{0}}&{...}&{\bf{0}}\\{\bf{0}}&{\bf{0}}&{\bf{1}}&{}&{\bf{0}}\\:&{}&{}&{}&:\\{\bf{0}}&{\bf{0}}&{\bf{0}}&{}&{\bf{1}}\\{ - {a_{\bf{0}}}}&{ - {a_{\bf{1}}}}&{ - {a_{\bf{2}}}}&{...}&{ - {a_{n - {\bf{1}}}}}\end{aligned}} \right)\).

21. Use mathematical induction to prove that for \(n \ge {\bf{2}}\),\(\begin{aligned}{c}det\left( {{C_p} - \lambda I} \right) = {\left( { - {\bf{1}}} \right)^n}\left( {{a_{\bf{0}}} + {a_{\bf{1}}}\lambda + ... + {a_{n - {\bf{1}}}}{\lambda ^{n - {\bf{1}}}} + {\lambda ^n}} \right)\\ = {\left( { - {\bf{1}}} \right)^n}p\left( \lambda \right)\end{aligned}\)

(Hint: Expanding by cofactors down the first column, show that \(det\left( {{C_p} - \lambda I} \right)\) has the form \(\left( { - \lambda B} \right) + {\left( { - {\bf{1}}} \right)^n}{a_{\bf{0}}}\) where \(B\) is a certain polynomial (by the induction assumption).)

Use Exercise 12 to find the eigenvalues of the matrices in Exercises 13 and 14.

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

Question: Is \(\lambda = - 2\) an eigenvalue of \(\left( {\begin{array}{*{20}{c}}7&3\\3&{ - 1}\end{array}} \right)\)? Why or why not?

Let \(A = \left( {\begin{aligned}{*{20}{c}}{.4}&{ - .3}\\{.4}&{1.2}\end{aligned}} \right)\). Explain why \({A^k}\) approaches \(\left( {\begin{aligned}{*{20}{c}}{ - .5}&{ - .75}\\1&{1.5}\end{aligned}} \right)\) as \(k \to \infty \).

Question: Construct a random integer-valued \(4 \times 4\) matrix \(A\).

  1. Reduce \(A\) to echelon form \(U\) with no row scaling, and use \(U\) in formula (1) (before Example 2) to compute \(\det A\). (If \(A\) happens to be singular, start over with a new random matrix.)
  2. Compute the eigenvalues of \(A\) and the product of these eigenvalues (as accurately as possible).
  3. List the matrix \(A\), and, to four decimal places, list the pivots in \(U\) and the eigenvalues of \(A\). Compute \(\det A\) with your matrix program, and compare it with the products you found in (a) and (b).
See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free