/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q7E Find an orthonormal basis of the... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

Find an orthonormal basis of the subspace spanned by the vectors in Exercise 3.

Short Answer

Expert verified

An orthonormal basis is \(\left\{ {\left( {\begin{aligned}{{}{}}{\frac{2}{{\sqrt {30} }}}\\{\frac{{ - 5}}{{\sqrt {30} }}}\\{\frac{1}{{\sqrt {30} }}}\end{aligned}} \right),\left( {\begin{aligned}{{}{}}{\frac{2}{{\sqrt 6 }}}\\{\frac{1}{{\sqrt 6 }}}\\{\frac{1}{{\sqrt 6 }}}\end{aligned}} \right)} \right\}\).

Step by step solution

01

Compute \(\left\| {{{\bf{v}}_1}} \right\|\) and \(\left\| {{{\bf{v}}_2}} \right\|\)

Let the vectors \({{\bf{v}}_1} = \left( {\begin{aligned}{{}{}}2\\{ - 5}\\1\end{aligned}} \right),{{\bf{v}}_2} = \left( {\begin{aligned}{{}{}}3\\{\frac{3}{2}}\\{\frac{3}{2}}\end{aligned}} \right)\)from Exercise 3.

Compute \(\left\| {{{\bf{v}}_1}} \right\|\) and \(\left\| {{{\bf{v}}_2}} \right\|\) as shown below:

\(\begin{aligned}{}\left\| {{{\bf{v}}_1}} \right\| &= \sqrt {{2^2} + {{\left( { - 5} \right)}^2} + {1^2}} \\ &= \sqrt {4 + 25 + 1} \\ &= \sqrt {30} \\\left\| {{{\bf{v}}_2}} \right\| &= \sqrt {{3^2} + {{\left( {\frac{3}{2}} \right)}^2} + {{\left( {\frac{3}{2}} \right)}^2}} \\ &= \sqrt {9 + \left( {\frac{9}{4}} \right) + \left( {\frac{9}{4}} \right)} \\ &= \sqrt {\frac{{54}}{4}} \\ &= \sqrt {\frac{{27}}{2}} \\ &= \frac{{3\sqrt 6 }}{2}\end{aligned}\)

02

Determine an orthonormal basis

Obtain an orthonormal basis as shown below:

\(\begin{aligned}{}\left\{ {\frac{{{{\bf{v}}_1}}}{{\left\| {{{\bf{v}}_1}} \right\|}},\frac{{{{\bf{v}}_2}}}{{\left\| {{{\bf{v}}_2}} \right\|}}} \right\} &= \left\{ {\frac{1}{{\sqrt {30} }}\left( {\begin{aligned}{{}{}}2\\{ - 5}\\1\end{aligned}} \right),\frac{1}{{\frac{{3\sqrt 6 }}{2}}}\left( {\begin{aligned}{{}{}}3\\{\frac{3}{2}}\\{\frac{3}{2}}\end{aligned}} \right)} \right\}\\ &= \left\{ {\left( {\begin{aligned}{{}{}}{\frac{2}{{\sqrt {30} }}}\\{\frac{{ - 5}}{{\sqrt {30} }}}\\{\frac{1}{{\sqrt {30} }}}\end{aligned}} \right),\left( {\begin{aligned}{{}{}}{\frac{2}{{\sqrt 6 }}}\\{\frac{1}{{\sqrt 6 }}}\\{\frac{1}{{\sqrt 6 }}}\end{aligned}} \right)} \right\}\end{aligned}\)

Hence, an orthonormal basis is\(\left\{ {\left( {\begin{aligned}{{}{}}{\frac{2}{{\sqrt {30} }}}\\{\frac{{ - 5}}{{\sqrt {30} }}}\\{\frac{1}{{\sqrt {30} }}}\end{aligned}} \right),\left( {\begin{aligned}{{}{}}{\frac{2}{{\sqrt 6 }}}\\{\frac{1}{{\sqrt 6 }}}\\{\frac{1}{{\sqrt 6 }}}\end{aligned}} \right)} \right\}\).

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 91Ó°ÊÓ!

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

In Exercises 1-6, the given set is a basis for a subspace W. Use the Gram-Schmidt process to produce an orthogonal basis for W.

6. \(\left( {\begin{aligned}{{}}3\\{ - 1}\\2\\{ - 1}\end{aligned}} \right),\left( {\begin{aligned}{{}}{ - 5}\\9\\{ - 9}\\3\end{aligned}} \right)\)

In Exercises 3–6, verify that\[\left\{ {{{\bf{u}}_1},{{\bf{u}}_2}} \right\}\]is an orthogonal set, and then find the orthogonal projection of\[y\]onto Span\[\left\{ {{{\bf{u}}_1},{{\bf{u}}_2}} \right\}\].

6.\[{\rm{y}} = \left[ {\begin{aligned}6\\4\\1\end{aligned}} \right]\],\[{{\bf{u}}_1} = \left[ {\begin{aligned}{ - 4}\\{ - 1}\\1\end{aligned}} \right]\],\[{{\bf{u}}_2} = \left[ {\begin{aligned}0\\1\\1\end{aligned}} \right]\]

In Exercises 1-4, find the equation \(y = {\beta _0} + {\beta _1}x\) of the least-square line that best fits the given data points.

  1. \(\left( { - 1,0} \right),\left( {0,1} \right),\left( {1,2} \right),\left( {2,4} \right)\)

In Exercises 1-4, find a least-sqaures solution of \(A{\bf{x}} = {\bf{b}}\) by (a) constructing a normal equations for \({\bf{\hat x}}\) and (b) solving for \({\bf{\hat x}}\).

3. \(A = \left( {\begin{aligned}{{}{}}{\bf{1}}&{ - {\bf{2}}}\\{ - {\bf{1}}}&{\bf{2}}\\{\bf{0}}&{\bf{3}}\\{\bf{2}}&{\bf{5}}\end{aligned}} \right)\), \({\bf{b}} = \left( {\begin{aligned}{{}{}}{\bf{3}}\\{\bf{1}}\\{ - {\bf{4}}}\\{\bf{2}}\end{aligned}} \right)\)

A certain experiment produce the data \(\left( {1,7.9} \right),\left( {2,5.4} \right)\) and \(\left( {3, - .9} \right)\). Describe the model that produces a least-squares fit of these points by a function of the form

\(y = A\cos x + B\sin x\)

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.