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Exercises 21–24 refer to \(V = C\left( {0,1} \right)\) with the inner product given by an integral, as in Example 7.

24. Compute \(\left\| g \right\|\) for \(g\) in Exercise 22.

Short Answer

Expert verified

The required value is \(\left\| g \right\| = \frac{1}{{\sqrt {105} }}\).

Step by step solution

01

Use the given information

For the pair of vectors\(\left\langle {f,g} \right\rangle \), the inner product is given by \(\left\langle {f,g} \right\rangle = \int_0^1 {f\left( t \right)g\left( t \right)dt} \).

It is given that \(g\left( t \right) = {t^3} - {t^2}\), then \(\left\langle {g,g} \right\rangle = \int_0^1 {g\left( t \right)g\left( t \right)dt} \)and\(\left\| g \right\| = \sqrt {\left\langle {g,g} \right\rangle } \).

02

Find the inner product

Plug the expression for\(g\left( t \right)\)into inner product\(\left\langle {g,g} \right\rangle = \int_0^1 {g\left( t \right)g\left( t \right)dt} \), as follows:

\(\begin{aligned}{}\left\langle {g,g} \right\rangle &= \int_0^1 {g\left( t \right)g\left( t \right)dt} \\ &= \int_0^1 {\left( {{t^3} - {t^2}} \right)\left( {{t^3} - {t^2}} \right)dt} \\ &= \int_0^1 {\left( {{t^6} - 2{t^5} + {t^4}} \right)\,dt} \\ &= \left( {\frac{{{t^7}}}{7} - \frac{{2{t^6}}}{6} + \frac{{{t^5}}}{5}} \right)_0^1\\ &= \left( {\frac{1}{7} - \frac{1}{3} + \frac{1}{5} - 0} \right)\\ &= \frac{1}{{105}}\end{aligned}\)

03

Compute \(\left\| g \right\|\) 

Plugthe expression for\(\left\langle {g,g} \right\rangle \)into\(\left\| g \right\| = \sqrt {\left\langle {g,g} \right\rangle } \)and simplify as follows:

\(\begin{aligned}{}\left\| g \right\| &= \sqrt {\left\langle {g,g} \right\rangle } \\ &= \sqrt {\frac{1}{{105}}} \\ &= \frac{1}{{\sqrt {105} }}\end{aligned}\)

Hence, the required value is, \(\left\| g \right\| = \frac{1}{{\sqrt {105} }}\).

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Most popular questions from this chapter

A Householder matrix, or an elementary reflector, has the form \(Q = I - 2{\bf{u}}{{\bf{u}}^T}\) where u is a unit vector. (See Exercise 13 in the Supplementary Exercise for Chapter 2.) Show that Q is an orthogonal matrix. (Elementary reflectors are often used in computer programs to produce a QR factorization of a matrix A. If A has linearly independent columns, then left-multiplication by a sequence of elementary reflectors can produce an upper triangular matrix.)

Let \({\mathbb{R}^{\bf{2}}}\) have the inner product of Example 1, and let \({\bf{x}} = \left( {{\bf{1}},{\bf{1}}} \right)\) and \({\bf{y}} = \left( {{\bf{5}}, - {\bf{1}}} \right)\).

a. Find\(\left\| {\bf{x}} \right\|\),\(\left\| {\bf{y}} \right\|\), and\({\left| {\left\langle {{\bf{x}},{\bf{y}}} \right\rangle } \right|^{\bf{2}}}\).

b. Describe all vectors\(\left( {{z_{\bf{1}}},{z_{\bf{2}}}} \right)\), that are orthogonal to y.

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 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 \(A\).

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

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

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