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Question:(M) Let \({{\rm{P}}_4}\) have the inner product as in Example 5, and let \({p_{0,}}{p_{1,\,}}{p_2}\)be the orthogonal polynomials from that example. Using your matrix program, apply the Gram–Schmidt process to the set\(\left\{ {{p_0},{p_{1\,}},{p_2},{t^3},{t^4}} \right\}\) to create an orthogonal basis for \({{\rm{P}}_4}\).

Short Answer

Expert verified

The new orthogonal polynomials are multiple of \( - 17t + 5{t^3}\)and\(72 - 155{t^2} + 35{t^4}\) .

Step by step solution

01

Use the given information

Let matrix A defines the basis \(A = \left\{ {{p_0},{p_1},{p_2},{t^3},{t^4}} \right\}\).

From example (5), polynomial vectors are:

\({p_0} = \left( {\begin{array}{*{20}{c}}1\\1\\1\\1\\1\end{array}} \right)\),\({p_1} = \left( {\begin{array}{*{20}{c}}{ - 2}\\{ - 1}\\0\\1\\2\end{array}} \right)\),\({p_2} = \left( {\begin{array}{*{20}{c}}2\\{ - 1}\\{ - 2}\\{ - 1}\\2\end{array}} \right)\)

Use the following steps to find the associated values for the obtained data in MATLAB.

  1. Formulate the matrix A using the polynomials \(\left\{ {{p_0},{p_1},{p_2}} \right\}\) and enter it in the tab,as \(\left( {\left( {\begin{array}{*{20}{c}}1&{ - 2}&4&1&1\\1&{ - 1}&1&1&1\\1&{\,\,\,0}&0&1&1\\1&{\,\,\,1}&1&1&1\\1&{\,\,\,2}&4&1&1\end{array}} \right)} \right)\).
  2. Run the command “gramschmidt(A)”.
  3. Press ENTER.

By using the matrix program, then new orthogonal polynomials are obtained as multiple of \( - 17t + 5{t^3}\)and\(72 - 155{t^2} + 35{t^4}\) .

02

Scale the polynomials

To obtain the small values of integers of the polynomials at \( - 2, - 1\), 0, 1 and 2, the polynomials must be scaled.

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Most popular questions from this chapter

[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 \(\left[ { - {\bf{2}}\pi ,{\bf{2}}\pi } \right]\).

Let \(U\) be an \(n \times n\) orthogonal matrix. Show that if \(\left\{ {{{\bf{v}}_1}, \ldots ,{{\bf{v}}_n}} \right\}\) is an orthonormal basis for \({\mathbb{R}^n}\), then so is \(\left\{ {U{{\bf{v}}_1}, \ldots ,U{{\bf{v}}_n}} \right\}\).

Compute the quantities in Exercises 1-8 using the vectors

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

7. \(\left\| {\mathop{\rm w}\nolimits} \right\|\)

Question: In Exercises 9-12, find (a) the orthogonal projection of b onto \({\bf{Col}}A\) and (b) a least-squares solution of \(A{\bf{x}} = {\bf{b}}\).

11. \(A = \left( {\begin{aligned}{{}{}}{\bf{4}}&{\bf{0}}&{\bf{1}}\\{\bf{1}}&{ - {\bf{5}}}&{\bf{1}}\\{\bf{6}}&{\bf{1}}&{\bf{0}}\\{\bf{1}}&{ - {\bf{1}}}&{ - {\bf{5}}}\end{aligned}} \right)\), \({\bf{b}} = \left( {\begin{aligned}{{}{}}{\bf{9}}\\{\bf{0}}\\{\bf{0}}\\{\bf{0}}\end{aligned}} \right)\)

In Exercises 13 and 14, the columns of Q were obtained by applying the Gram-Schmidt process to the columns of A. Find an upper triangular matrix R such that \(A = QR\). Check your work.

13. \(A = \left( {\begin{aligned}{{}{}}5&9\\1&7\\{ - 3}&{ - 5}\\1&5\end{aligned}} \right),{\rm{ }}Q = \left( {\begin{aligned}{{}{}}{\frac{5}{6}}&{ - \frac{1}{6}}\\{\frac{1}{6}}&{\frac{5}{6}}\\{ - \frac{3}{6}}&{\frac{1}{6}}\\{\frac{1}{6}}&{\frac{3}{6}}\end{aligned}} \right)\)

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