Question:Let \(V\) be the space \(C\left( { - 1,1} \right)\) with the inner product of Example 7. Find an orthogonal basis for the subspace spanned by the polynomials 1, \(t\), and \({t^2}\). The polynomials in this basis are calledLegendre polynomials.

Short Answer

Expert verified

The orthogonal basis is \(\left\{ {1,\,t,\,3{t^2} - 1} \right\}\).

Step by step solution

01

Use the given information

If the pair of vectors\(\left\langle {f,g} \right\rangle \)belong to vector space \(V\) defined in \(C\left( { - 1,1} \right)\), then their inner product is given by \(\left\langle {f,g} \right\rangle = \int_{ - 1}^1 {f\left( t \right)g\left( t \right)dt} \).

It is given that \(1,\,t,\,{t^2}\) are orthogonal, then \(\left\langle {1,t} \right\rangle \) must be 0, that is\(\int_{ - 1}^1 {tdt} = 0\).

02

Use Gram Schmidt process

According to the Gram Schmidt process, the third element in the orthogonal basis span\(\left\{ {1,t,{t^2}} \right\}\)can be defined as\({t^2} - \frac{{\left\langle {{t^2},1} \right\rangle }}{{\left\langle {1,1} \right\rangle }}1 - \frac{{\left\langle {{t^2},1} \right\rangle }}{{\left\langle {t,t} \right\rangle }}t\).

Find\(\left\langle {{t^2},1} \right\rangle ,\,\left\langle {1,1} \right\rangle ,\,\left\langle {t,t} \right\rangle \), as follows:

\(\begin{aligned}{}\left\langle {t,t} \right\rangle &= \int_{ - 1}^1 {{t^2}dt} \\ &= \left( {\frac{{{t^3}}}{3}} \right)_{ - 1}^1\\ &= \left( {\frac{1}{3} - \left( { - \frac{1}{3}} \right)} \right)\\ &= \frac{2}{3}\end{aligned}\)

\(\begin{aligned}{}\left\langle {1,1} \right\rangle &= \int_{ - 1}^1 {1dt} \\ &= \left( t \right)_{ - 1}^1\\ &= \left( {1 - \left( { - 1} \right)} \right)\\ &= 2\end{aligned}\)

\(\begin{aligned}{}\left\langle {{t^2},t} \right\rangle &= \int_{ - 1}^1 {{t^3}dt} \\ &= \left( {\frac{{{t^4}}}{4}} \right)_{ - 1}^1\\& = \left( {\frac{1}{4} - \frac{1}{4}} \right)\\ &= 0\end{aligned}\)

03

Simplify for Gram Schmidt inequality

Plug the above obtained values in \({t^2} - \frac{{\left\langle {{t^2},1} \right\rangle }}{{\left\langle {1,1} \right\rangle }}1 - \frac{{\left\langle {{t^2},1} \right\rangle }}{{\left\langle {t,t} \right\rangle }}t\) and simplify as follows:

\(\begin{aligned}{}{t^2} - \frac{{\left\langle {{t^2},1} \right\rangle }}{{\left\langle {1,1} \right\rangle }}1 - \frac{{\left\langle {{t^2},t} \right\rangle }}{{\left\langle {t,t} \right\rangle }}t &= {t^2} - \frac{{2/3}}{2}1 - \left( 0 \right)t\\ &= {t^2} - \frac{1}{3}\end{aligned}\)

The third element in the orthogonal basis for subspace spanned by the polynomials \(1,\,t,\,{t^2}\)can be obtained by scaling\({t^2} - \frac{1}{3}\)by 3, to get it as\(3{t^2} - 1\).

Thus, the orthogonal basis is \(\left\{ {1,\,t,\,3{t^2} - 1} \right\}\).

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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. \(\left( {1,0} \right),\left( {2,1} \right),\left( {4,2} \right),\left( {5,3} \right)\)

Let \(X\) be the design matrix used to find the least square line of fit data \(\left( {{x_1},{y_1}} \right), \ldots ,\left( {{x_n},{y_n}} \right)\). Use a theorem in Section 6.5 to show that the normal equations have a unique solution if and only if the data include at least two data points with different \(x\)-coordinates.

Compute the quantities in Exercises 1-8 using the vectors

\({\mathop{\rm u}\nolimits} = \left( {\begin{aligned}{*{20}{c}}{ - 1}\\2\end{aligned}} \right),{\rm{ }}{\mathop{\rm v}\nolimits} = \left( {\begin{aligned}{*{20}{c}}4\\6\end{aligned}} \right),{\rm{ }}{\mathop{\rm w}\nolimits} = \left( {\begin{aligned}{*{20}{c}}3\\{ - 1}\\{ - 5}\end{aligned}} \right),{\rm{ }}{\mathop{\rm x}\nolimits} = \left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\\3\end{aligned}} \right)\)

5. \(\left( {\frac{{{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm v}\nolimits} }}{{{\mathop{\rm v}\nolimits} \cdot {\mathop{\rm v}\nolimits} }}} \right){\mathop{\rm v}\nolimits} \)

In Exercises 11 and 12, find the closest point to\[{\bf{y}}\]in the subspace\[W\]spanned by\[{{\bf{v}}_1}\], and\[{{\bf{v}}_2}\].

11.\[y = \left[ {\begin{aligned}3\\1\\5\\1\end{aligned}} \right]\],\[{{\bf{v}}_1} = \left[ {\begin{aligned}3\\1\\{ - 1}\\1\end{aligned}} \right]\],\[{{\bf{v}}_2} = \left[ {\begin{aligned}1\\{ - 1}\\1\\{ - 1}\end{aligned}} \right]\]

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