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

Given \(a \ge 0\) and \(b \ge 0\), let \({\rm{u}} = \left( \begin{array}{l}\sqrt a \\\sqrt b \end{array} \right)\)and\({\rm{v}} = \left( \begin{array}{l}\sqrt b \\\sqrt a \end{array} \right)\). Use the Cauchy–Schwarz inequality to compare the geometric mean \(\sqrt {ab} \) with the arithmetic mean \(\frac{{\left( {a + b} \right)}}{2}\).

Short Answer

Expert verified

The required inequality is \(2\sqrt {ab} \le a + b\).

Step by step solution

01

Use the given information

It is given that \({\rm{u}} = \left( \begin{array}{l}\sqrt a \\\sqrt b \end{array} \right)\) and \({\rm{v}} = \left( \begin{array}{l}\sqrt b \\\sqrt a \end{array} \right)\). So, according to inner product axioms, \({\left\| {\rm{u}} \right\|^2} = a + b\) and \({\left\| {\rm{v}} \right\|^2} = a + b\)and\(\left| {\left\langle {{\rm{u,v}}} \right\rangle } \right| = 2\sqrt {ab} \).

02

Use Cauchy Schwarz inequality

According to Cauchy Schwarz inequality, an inner product on a vector space \(V\) is a function that, to each pair of vectors \({\bf{u}}\) and \({\rm{v}}\) in \(V\), associates a real number \(\left\langle {{\bf{u}},{\rm{v}}} \right\rangle \)and satisfies the axiom, \(\left| {\left\langle {{\bf{u}},{\rm{v}}} \right\rangle } \right| \le \left\| {\rm{u}} \right\|\left\| {\rm{v}} \right\|\) for all \({\bf{u}}\) and \({\rm{v}}\)in \(V\).

Plug the above obtained values in Cauchy Schwarz inequality, as follows:

\(\begin{array}{c}\left\langle {{\rm{u,v}}} \right\rangle \le \left\| {\rm{u}} \right\|\left\| {\rm{v}} \right\|\\2\sqrt {ab} \le \sqrt {a + b} \sqrt {a + b} \\2\sqrt {ab} \le a + b\end{array}\)

Thus, the required inequality is\(2\sqrt {ab} \le a + b\).

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

Find an orthogonal basis for the column space of each matrix in Exercises 9-12.

12. \(\left( {\begin{aligned}{{}{}}1&3&5\\{ - 1}&{ - 3}&1\\0&2&3\\1&5&2\\1&5&8\end{aligned}} \right)\)

Given data for a least-squares problem, \(\left( {{x_1},{y_1}} \right), \ldots ,\left( {{x_n},{y_n}} \right)\), the following abbreviations are helpful:

\(\begin{aligned}{l}\sum x = \sum\nolimits_{i = 1}^n {{x_i}} ,{\rm{ }}\sum {{x^2}} = \sum\nolimits_{i = 1}^n {x_i^2} ,\\\sum y = \sum\nolimits_{i = 1}^n {{y_i}} ,{\rm{ }}\sum {xy} = \sum\nolimits_{i = 1}^n {{x_i}{y_i}} \end{aligned}\)

The normal equations for a least-squares line \(y = {\hat \beta _0} + {\hat \beta _1}x\) may be written in the form

\(\begin{aligned}{c}{{\hat \beta }_0} + {{\hat \beta }_1}\sum x = \sum y \\{{\hat \beta }_0}\sum x + {{\hat \beta }_1}\sum {{x^2}} = \sum {xy} {\rm{ (7)}}\end{aligned}\)

Derive the normal equations (7) from the matrix form given in this section.

In Exercises 5 and 6, describe all least squares solutions of the equation \(A{\bf{x}} = {\bf{b}}\).

6.\(A = \left( {\begin{aligned}{{}{}}{\bf{1}}&{\bf{1}}&{\bf{0}}\\{\bf{1}}&{\bf{1}}&{\bf{0}}\\{\bf{1}}&{\bf{1}}&{\bf{0}}\\{\bf{1}}&{\bf{0}}&{\bf{1}}\\{\bf{1}}&{\bf{0}}&{\bf{1}}\\{\bf{1}}&{\bf{0}}&{\bf{1}}\end{aligned}} \right)\),\({\bf{b}} = \left( {\begin{aligned}{{}{}}{\bf{7}}\\{\bf{2}}\\{\bf{3}}\\{\bf{6}}\\{\bf{5}}\\{\bf{4}}\end{aligned}} \right)\)

Compute the least-squares error associated with the least square solution found in Exercise 3.

Exercises 13 and 14, the columns of \(Q\) were obtained by applying the Gram Schmidt process to the columns of \(A\). Find anupper triangular matrix \(R\) such that \(A = QR\). Check your work.

14.\(A = \left( {\begin{aligned}{{}{r}}{ - 2}&3\\5&7\\2&{ - 2}\\4&6\end{aligned}} \right)\), \(Q = \left( {\begin{aligned}{{}{r}}{\frac{{ - 2}}{7}}&{\frac{5}{7}}\\{\frac{5}{7}}&{\frac{2}{7}}\\{\frac{2}{7}}&{\frac{{ - 4}}{7}}\\{\frac{4}{7}}&{\frac{2}{7}}\end{aligned}} \right)\)

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