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Question 14: Let \({\mathop{\rm y}\nolimits} = \left( {\begin{array}{*{20}{c}}2\\6\end{array}} \right)\), and \({\mathop{\rm u}\nolimits} = \left( {\begin{array}{*{20}{c}}7\\1\end{array}} \right)\). Write y as the sum of a vector in \({\mathop{\rm Span}\nolimits} \left\{ {\mathop{\rm u}\nolimits} \right\}\) and a vector orthogonal to u.

Short Answer

Expert verified

The sum of two orthogonal vectors is \({\mathop{\rm y}\nolimits} = \left( {\begin{array}{*{20}{c}}{\frac{{14}}{5}}\\{\frac{2}{5}}\end{array}} \right) + \left( {\begin{array}{*{20}{c}}{\frac{{ - 4}}{5}}\\{\frac{{28}}{5}}\end{array}} \right)\).

Step by step solution

01

Definition of orthogonal projection

Consider a vector y in \({\mathbb{R}^n}\). Then,

\({\mathop{\rm y}\nolimits} = \widehat {\mathop{\rm y}\nolimits} + {\mathop{\rm z}\nolimits} \)…. (1)

Where \(\widehat {\mathop{\rm y}\nolimits} = \alpha {\mathop{\rm z}\nolimits} \) for any scalar \(\alpha \) and z denotes any vector orthogonal to u. Consider \({\mathop{\rm z}\nolimits} = {\mathop{\rm y}\nolimits} - \alpha {\mathop{\rm u}\nolimits} \), therefore, that equation (1) is satisfied. Then \({\mathop{\rm y}\nolimits} - \widehat {\mathop{\rm y}\nolimits} \) is orthogonal to u such that if the equation (1) is satisfied with z orthogonal to u such that if \(\alpha = \frac{{{\mathop{\rm y}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{{{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}\), and \(\widehat {\mathop{\rm y}\nolimits} = \frac{{{\mathop{\rm y}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{{{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{\mathop{\rm u}\nolimits} \).

The vector \(\widehat {\mathop{\rm y}\nolimits} \) is known as the orthogonal projection of y onto uand, the vector z is known as thecomponentof y orthogonal to u. Typically, \(\widehat {\mathop{\rm y}\nolimits} \) is represented by \({{\mathop{\rm proj}\nolimits} _L}{\mathop{\rm y}\nolimits} \) and is called the orthogonal projection of y onto L.

\(\widehat {\mathop{\rm y}\nolimits} = {{\mathop{\rm proj}\nolimits} _L}{\mathop{\rm y}\nolimits} = \frac{{{\mathop{\rm y}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{{{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{\mathop{\rm u}\nolimits} \)

02

Compute the orthogonal projection of y onto u

Compute \({\mathop{\rm y}\nolimits} \cdot {\mathop{\rm u}\nolimits} \) and \({\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} \) as shown below:

\(\begin{array}{c}{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm y}\nolimits} = \left( {\begin{array}{*{20}{c}}7\\1\end{array}} \right) \cdot \left( {\begin{array}{*{20}{c}}2\\6\end{array}} \right)\\ = 20\\{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} = \left( {\begin{array}{*{20}{c}}7\\1\end{array}} \right) \cdot \left( {\begin{array}{*{20}{c}}7\\1\end{array}} \right)\\ = 50\end{array}\)

Obtain the orthogonal projection of \({\mathop{\rm y}\nolimits} \) onto \({\mathop{\rm u}\nolimits} \) as shown below:

\(\begin{array}{c}\widehat {\mathop{\rm y}\nolimits} = \frac{{{\mathop{\rm y}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{{{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{\mathop{\rm u}\nolimits} \\ = \frac{{20}}{{50}}\left( {\begin{array}{*{20}{c}}7\\1\end{array}} \right)\\ = \frac{2}{5}\left( {\begin{array}{*{20}{c}}7\\1\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}{\frac{{14}}{5}}\\{\frac{2}{5}}\end{array}} \right)\end{array}\)

Thus, the orthogonal projection of \({\mathop{\rm y}\nolimits} \) onto \({\mathop{\rm u}\nolimits} \) is \(\widehat {\mathop{\rm y}\nolimits} = \left( {\begin{array}{*{20}{c}}{\frac{{14}}{5}}\\{\frac{2}{5}}\end{array}} \right)\).

03

Compute the component of y orthogonal to u

Obtain the component of \({\mathop{\rm y}\nolimits} \) orthogonal to \({\mathop{\rm u}\nolimits} \) as shown below:

\(\begin{array}{c}{\mathop{\rm y}\nolimits} - \widehat {\mathop{\rm y}\nolimits} = \left( {\begin{array}{*{20}{c}}2\\6\end{array}} \right) - \left( {\begin{array}{*{20}{c}}{\frac{{14}}{5}}\\{\frac{2}{5}}\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}{2 - \frac{{14}}{5}}\\{6 - \frac{2}{5}}\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}{\frac{{ - 4}}{5}}\\{\frac{{28}}{5}}\end{array}} \right)\end{array}\)

Therefore, the component of \({\mathop{\rm y}\nolimits} \) orthogonal to \({\mathop{\rm u}\nolimits} \) is \({\mathop{\rm y}\nolimits} - \widehat {\mathop{\rm y}\nolimits} = \left( {\begin{array}{*{20}{c}}{\frac{{ - 4}}{5}}\\{\frac{{28}}{5}}\end{array}} \right)\).

04

Write y as the sum of two orthogonal vectors

Write \({\mathop{\rm y}\nolimits} \) as the sum of two orthogonal vectors as shown below:

\(\begin{array}{c}{\mathop{\rm y}\nolimits} = \widehat {\mathop{\rm y}\nolimits} + \left( {{\mathop{\rm y}\nolimits} - \widehat {\mathop{\rm y}\nolimits} } \right)\\ = \left( {\begin{array}{*{20}{c}}{\frac{{14}}{5}}\\{\frac{2}{5}}\end{array}} \right) + \left( {\begin{array}{*{20}{c}}{\frac{{ - 4}}{5}}\\{\frac{{28}}{5}}\end{array}} \right)\end{array}\)

Thus, the sum of two orthogonal vectors is \({\mathop{\rm y}\nolimits} = \left( {\begin{array}{*{20}{c}}{\frac{{14}}{5}}\\{\frac{2}{5}}\end{array}} \right) + \left( {\begin{array}{*{20}{c}}{\frac{{ - 4}}{5}}\\{\frac{{28}}{5}}\end{array}} \right)\).

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Most popular questions from this chapter

In Exercises 7–10, let\[W\]be the subspace spanned by the\[{\bf{u}}\]’s, and write y as the sum of a vector in\[W\]and a vector orthogonal to\[W\].

9.\[y = \left[ {\begin{aligned}4\\3\\3\\{ - 1}\end{aligned}} \right]\],\[{{\bf{u}}_1} = \left[ {\begin{aligned}1\\1\\0\\1\end{aligned}} \right]\],\[{{\bf{u}}_2} = \left[ {\begin{aligned}{ - 1}\\3\\1\\{ - 2}\end{aligned}} \right]\],\[{{\bf{u}}_2} = \left[ {\begin{aligned}{ - 1}\\0\\1\\1\end{aligned}} \right]\]

Suppose \(A = QR\), where \(Q\) is \(m \times n\) and R is \(n \times n\). Showthat if the columns of \(A\) are linearly independent, then \(R\) mustbe invertible.

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

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

3. \(\left( {\begin{aligned}{{}{}}2\\{ - 5}\\1\end{aligned}} \right),\left( {\begin{aligned}{{}{}}4\\{ - 1}\\2\end{aligned}} \right)\)

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