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Verify the parallelogram law for vectors \({\bf{u}}\) and \({\bf{v}}\) in \({\mathbb{R}^3}\):\({\left\| {{\bf{u}} + {\bf{v}}} \right\|^2} + {\left\| {{\bf{u}} - {\bf{v}}} \right\|^2} = 2{\left\| {\bf{u}} \right\|^2} + 2{\left\| {\bf{v}} \right\|^2}\).

Short Answer

Expert verified

It is verified that, \({\left\| {{\bf{u}} + {\bf{v}}} \right\|^2} + {\left\| {{\bf{u}} - {\bf{v}}} \right\|^2} = 2{\left\| {\bf{u}} \right\|^2} + 2{\left\| {\bf{v}} \right\|^2}\).

Step by step solution

01

 Find \({\left\| {\bf{u}} \right\|^2},{\left\| {\bf{v}} \right\|^2},{\rm{ and }}{\left\| {{\bf{u}} + {\bf{v}}} \right\|^2},{\left\| {{\bf{u}} - {\bf{v}}} \right\|^2}\)

Find \({\left\| {\bf{u}} \right\|^2}\) and \({\left\| {\bf{v}} \right\|^2}\).

\(\begin{array}{l}{\left\| {\bf{u}} \right\|^2} &= {\bf{u}} \cdot {\bf{u}}\\{\left\| {\bf{v}} \right\|^2} &= {\bf{v}} \cdot {\bf{v}}\end{array}\)

Find \({\left\| {{\bf{u}} + {\bf{v}}} \right\|^2}\) and \({\left\| {{\bf{u}} - {\bf{v}}} \right\|^2}\).

\(\begin{aligned}{c}{\left\| {{\bf{u}} + {\bf{v}}} \right\|^2} &= \left( {{\bf{u}} + {\bf{v}}} \right) \cdot \left( {{\bf{u}} + {\bf{v}}} \right)\\ &= {\bf{u}} \cdot {\bf{u}} + 2{\bf{u}} \cdot {\bf{v}} + {\bf{v}} \cdot {\bf{v}}\end{aligned}\)

\(\begin{aligned}{c}{\left\| {{\bf{u}} - {\bf{v}}} \right\|^2} &= \left( {{\bf{u}} - {\bf{v}}} \right) \cdot \left( {{\bf{u}} - {\bf{v}}} \right)\\ &= {\bf{u}} \cdot {\bf{u}} - 2{\bf{u}} \cdot {\bf{v}} + {\bf{v}} \cdot {\bf{v}}\end{aligned}\)

02

 Find the sum of obtained values

Find the sum of \({\left\| {\bf{u}} \right\|^2}\) and \({\left\| {\bf{v}} \right\|^2}\).

\({\left\| {\bf{u}} \right\|^2} + {\left\| {\bf{v}} \right\|^2} = {\bf{u}} \cdot {\bf{u}} + {\bf{v}} \cdot {\bf{v}}{\rm{ }}\left( 1 \right)\)

Find the sum of \({\left\| {{\bf{u}} + {\bf{v}}} \right\|^2}\) and \({\left\| {{\bf{u}} - {\bf{v}}} \right\|^2}\).

\(\begin{aligned}{c}{\left\| {{\bf{u}} + {\bf{v}}} \right\|^2} + {\left\| {{\bf{u}} - {\bf{v}}} \right\|^2} &= \left( {{\bf{u}} + {\bf{v}}} \right) \cdot \left( {{\bf{u}} + {\bf{v}}} \right) + \left( {{\bf{u}} - {\bf{v}}} \right) \cdot \left( {{\bf{u}} - {\bf{v}}} \right)\\ &= {\bf{u}} \cdot {\bf{u}} + 2{\bf{u}} \cdot {\bf{v}} + {\bf{v}} \cdot {\bf{v}} + {\bf{u}} \cdot {\bf{u}} - 2{\bf{u}} \cdot {\bf{v}} + {\bf{v}} \cdot {\bf{v}}\\ &= 2{\bf{u}} \cdot {\bf{u}} + 2{\bf{v}} \cdot {\bf{v}}\end{aligned}\)

Use equation (1) in the obtained expression.

\({\left\| {{\bf{u}} + {\bf{v}}} \right\|^2} + {\left\| {{\bf{u}} - {\bf{v}}} \right\|^2} = 2{\left\| {\bf{u}} \right\|^2} + 2{\left\| {\bf{v}} \right\|^2}\)

Hence, the parallelogram law is proved.

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Most popular questions from this chapter

Let \({\mathbb{R}^{\bf{2}}}\) have the inner product of Example 1. Show that the Cauchy-Schwarz inequality holds for \({\bf{x}} = \left( {{\bf{3}}, - {\bf{2}}} \right)\) and \({\bf{y}} = \left( { - {\bf{2}},{\bf{1}}} \right)\). (Suggestion: Study \({\left| {\left\langle {{\bf{x}},{\bf{y}}} \right\rangle } \right|^{\bf{2}}}\).)

Suppose the x-coordinates of the data \(\left( {{x_1},{y_1}} \right), \ldots ,\left( {{x_n},{y_n}} \right)\) are in mean deviation form, so that \(\sum {{x_i}} = 0\). Show that if \(X\) is the design matrix for the least-squares line in this case, then \({X^T}X\) is a diagonal matrix.

(M) Use the method in this section to produce a \(QR\) factorization of the matrix in Exercise 24.

In Exercises 17 and 18, all vectors and subspaces are in \({\mathbb{R}^n}\). Mark each statement True or False. Justify each answer.

a. If \(W = {\rm{span}}\left\{ {{x_1},{x_2},{x_3}} \right\}\) with \({x_1},{x_2},{x_3}\) linearly independent,

and if \(\left\{ {{v_1},{v_2},{v_3}} \right\}\) is an orthogonal set in \(W\) , then \(\left\{ {{v_1},{v_2},{v_3}} \right\}\) is a basis for \(W\) .

b. If \(x\) is not in a subspace \(W\) , then \(x - {\rm{pro}}{{\rm{j}}_W}x\) is not zero.

c. In a \(QR\) factorization, say \(A = QR\) (when \(A\) has linearly

independent columns), the columns of \(Q\) form an

orthonormal basis for the column space of \(A\).

In Exercises 13 and 14, find the best approximation to\[{\bf{z}}\]by vectors of the form\[{c_1}{{\bf{v}}_1} + {c_2}{{\bf{v}}_2}\].

13.\[z = \left[ {\begin{aligned}3\\{ - 7}\\2\\3\end{aligned}} \right]\],\[{{\bf{v}}_1} = \left[ {\begin{aligned}2\\{ - 1}\\{ - 3}\\1\end{aligned}} \right]\],\[{{\bf{v}}_2} = \left[ {\begin{aligned}1\\1\\0\\{ - 1}\end{aligned}} \right]\]

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