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In exercises 7-10, show that {u1, u2} or {u1,u2,u3} is an orthogonal basis for \({\mathbb{R}^2}\) or \({\mathbb{R}^3}\), respectively. Then express x as a linear combination of the u.

7. \[{u_1} = \left[ {\begin{align}2\\{ - 3}\end{align}} \right]\], \[{u_2} = \left[ {\begin{align}6\\4\end{align}} \right]\], and \[x = \left[ {\begin{align}9\\{ - 7}\end{align}} \right]\]

Short Answer

Expert verified

The required linear combination is, \[x = 3{u_1} + \frac{1}{2}{u_2}\].

Step by step solution

01

Linear combination definition

Let the set of vectors \({u_1},.....,{u_p}\) be an orthogonal basis for a subspace \(W\) of \({\mathbb{R}^n}\) and the linear combination is given by \(y = {c_1}{u_1} + ..... + {c_p}{u_p}\) , then the weights in the linear combination are given as \({c_j} = \frac{{y \cdot {u_j}}}{{{u_j} \cdot {u_j}}}\), for each \(y\) in \(W\).

02

Check for orthogonality of given vectors

Find \({u_1} \cdot {u_2}\) as follows:

\(\begin{array}{c}{u_1} \cdot {u_2} = \left( 2 \right)\left( 6 \right) + \left( { - 3} \right)\left( 4 \right)\\ = 12 - 12\\ = 0\end{array}\)

Hence, the vectors are orthogonal to each other, as the vectors are non-zero and linearly independent. Therefore, the given set form a basis for \({\mathbb{R}^2}\).

03

Express x as a linear combination

The vector x can be expressed as a linear combination as follows:

\[\begin{align}{c}x = \left( {\frac{{x \cdot {u_1}}}{{{u_1} \cdot {u_1}}}} \right){u_1} + \left( {\frac{{x \cdot {u_2}}}{{{u_2} \cdot {u_2}}}} \right){u_2}\\ = \left( {\frac{{\left( 9 \right)\left( 2 \right) + \left( { - 7} \right)\left( { - 3} \right)}}{{\left( 2 \right)\left( 2 \right) + \left( { - 3} \right)\left( { - 3} \right)}}} \right){u_1} + \left( {\frac{{\left( 9 \right)\left( 6 \right) + \left( { - 7} \right)\left( 4 \right)}}{{\left( 6 \right)\left( 6 \right) + \left( 4 \right)\left( 4 \right)}}} \right){u_2}\\ = \left( {\frac{{18 + 21}}{{4 + 9}}} \right){u_1} + \left( {\frac{{54 - 28}}{{36 + 16}}} \right){u_2}\\ = \left( {\frac{{18 + 2}}{{4 + 9}}} \right){u_1} + \left( {\frac{{54 - 28}}{{36 + 16}}} \right){u_2}\,\\ = 3{u_1} + \frac{1}{2}{u_2}\end{align}\]

Hence, \[x = 3{u_1} + \frac{1}{2}{u_2}\].

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Most popular questions from this chapter

Suppose radioactive substance A and B have decay constants of \(.02\) and \(.07\), respectively. If a mixture of these two substances at a time \(t = 0\) contains \({M_A}\) grams of \(A\) and \({M_B}\) grams of \(B\), then a model for the total amount of mixture present at time \(t\) is

\(y = {M_A}{e^{ - .02t}} + {M_B}{e^{ - .07t}}\) (6)

Suppose the initial amounts \({M_A}\) and are unknown, but a scientist is able to measure the total amounts present at several times and records the following points \(\left( {{t_i},{y_i}} \right):\left( {10,21.34} \right),\left( {11,20.68} \right),\left( {12,20.05} \right),\left( {14,18.87} \right)\) and \(\left( {15,18.30} \right)\).

a.Describe a linear model that can be used to estimate \({M_A}\) and \({M_B}\).

b. Find the least-squares curved based on (6).

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

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.

[M] Let \({f_{\bf{4}}}\) and \({f_{\bf{5}}}\) be the fourth-order and fifth order Fourier approximations in \(C\left[ {{\bf{0}},{\bf{2}}\pi } \right]\) to the square wave function in Exercise 10. Produce separate graphs of \({f_{\bf{4}}}\) and \({f_{\bf{5}}}\) on the interval \(\left[ {{\bf{0}},{\bf{2}}\pi } \right]\), and produce graph of \({f_{\bf{5}}}\) on \(\left[ { - {\bf{2}}\pi ,{\bf{2}}\pi } \right]\).

Given \(A = QR\) as in Theorem 12, describe how to find an orthogonal\(m \times m\)(square) matrix \({Q_1}\) and an invertible \(n \times n\) upper triangular matrix \(R\) such that

\(A = {Q_1}\left[ {\begin{aligned}{{}{}}R\\0\end{aligned}} \right]\)

The MATLAB qr command supplies this 鈥渇ull鈥 QR factorization

when rank \(A = n\).

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