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

In Exercises 25-28, determine if the specified linear transformation is (a) one-to-one and (b) onto. Justify each answer.

25. The transformation in Exercise 17.

Short Answer

Expert verified

The specified linear transformation is neither one-to-one nor onto.

Step by step solution

01

The transformation in Exercise 17\(T\left( {{x_1},{x_2},{x_3},{x_4}} \right) = \left( {0,{x_1} + {x_2},{x_2} + {x_3},{x_3} + {x_4}} \right)\)

Write the transformation in Exercise 17.

02

Determine the standard matrix of \(T\) by inspection

Write the transformation \(T\left( x \right)\) and \(x\) as the column vectors and fill in the entries in \(A\).

\(\begin{array}{c}T\left( x \right) = \left[ {\begin{array}{*{20}{c}}0\\{{x_1} + {x_2}}\\{{x_2} + {x_3}}\\{{x_3} + {x_4}}\end{array}} \right]\\ = \left[ A \right]\left[ {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}0&0&0&0\\1&1&0&0\\0&1&1&0\\0&0&1&1\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right]\end{array}\)

03

Apply row operation on the standard matrix of \(T\)

Interchange row 1 and row 2.

\(\left[ {\begin{array}{*{20}{c}}1&1&0&0\\0&0&0&0\\0&1&1&0\\0&0&1&1\end{array}} \right]\)

Interchange row 2 and row 3, and row 3 and row 4.

\(\left[ {\begin{array}{*{20}{c}}1&1&0&0\\0&1&1&0\\0&0&1&1\\0&0&0&0\end{array}} \right]\)

04

Determine whether the linear transformation is one-to-one or onto

Theorem 11states that let \(T:{\mathbb{R}^n} \to {\mathbb{R}^m}\) be a linear transformation, then \(T\) is one-to-one if and only if the equation \(T\left( x \right) = 0\) has only a trivial solution.

Theorem 12states that let \(T:{\mathbb{R}^n} \to {\mathbb{R}^m}\) be a linear transformation, and let \(A\) be the standard matrix \(T\) then \(T\) maps \[{\mathbb{R}^n}\] onto \[{\mathbb{R}^m}\] if and only if the columns of \(A\) span \[{\mathbb{R}^m}\].

There are only three pivot positions in the matrix \(A\); so the equation \(Ax = 0\) has a nontrivial solution. The transformation \(T\) is not one-to-one, according to theorem 11. In addition, the column of \(A\) does not span \({\mathbb{R}^4}\) because \(A\) does not have a pivot in each row. \(T\) cannot map \({\mathbb{R}^4}\) onto \({\mathbb{R}^4}\), according to theorem 12.

Thus, the specified linear transformation is neither one-to-one nor onto.

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

Suppose an experiment leads to the following system of equations:

\(\begin{aligned}{c}{\bf{4}}.{\bf{5}}{x_{\bf{1}}} + {\bf{3}}.{\bf{1}}{x_{\bf{2}}} = {\bf{19}}.{\bf{249}}\\1.6{x_{\bf{1}}} + 1.1{x_{\bf{2}}} = 6.843\end{aligned}\) (3)

  1. Solve system (3), and then solve system (4), below, in which the data on the right have been rounded to two decimal places. In each case, find the exactsolution.

\(\begin{aligned}{c}{\bf{4}}.{\bf{5}}{x_{\bf{1}}} + {\bf{3}}.{\bf{1}}{x_{\bf{2}}} = {\bf{19}}.{\bf{25}}\\1.6{x_{\bf{1}}} + 1.1{x_{\bf{2}}} = 6.8{\bf{4}}\end{aligned}\) (4)

  1. The entries in (4) differ from those in (3) by less than .05%. Find the percentage error when using the solution of (4) as an approximation for the solution of (3).
  1. Use your matrix program to produce the condition number of the coefficient matrix in (3).

Let \(T:{\mathbb{R}^n} \to {\mathbb{R}^n}\) be an invertible linear transformation, and let Sand U be functions from \({\mathbb{R}^n}\) into \({\mathbb{R}^n}\) such that \(S\left( {T\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \) and \(\)\(U\left( {T\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \) for all x in \({\mathbb{R}^n}\). Show that \(U\left( v \right) = S\left( v \right)\) for all v in \({\mathbb{R}^n}\). This will show that Thas a unique inverse, as asserted in theorem 9. (Hint: Given any v in \({\mathbb{R}^n}\), we can write \({\mathop{\rm v}\nolimits} = T\left( {\mathop{\rm x}\nolimits} \right)\) for some x. Why? Compute \(S\left( {\mathop{\rm v}\nolimits} \right)\) and \(U\left( {\mathop{\rm v}\nolimits} \right)\)).

Find the general solutions of the systems whose augmented matrices are given as

14. \(\left[ {\begin{array}{*{20}{c}}1&2&{ - 5}&{ - 6}&0&{ - 5}\\0&1&{ - 6}&{ - 3}&0&2\\0&0&0&0&1&0\\0&0&0&0&0&0\end{array}} \right]\).

Let \(T:{\mathbb{R}^n} \to {\mathbb{R}^m}\) be a linear transformation, and suppose \(T\left( u \right) = {\mathop{\rm v}\nolimits} \). Show that \(T\left( { - u} \right) = - {\mathop{\rm v}\nolimits} \).

Let T be a linear transformation that maps \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\). Is \({T^{ - 1}}\) also one-to-one?

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