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Using paper and pencil, perform the Gram-Schmidt process on the sequences of vectors given in Exercises 1 through 14.

8.[5422],[367-2]

Short Answer

Expert verified

The orthonormal vectors of the sequence [5422],[367-2]is[5/74/72/72/7],-2/72/75/7-4/7.

Step by step solution

01

Determine the Gram-Schmidt process

Consider a basis of a subspace VofRnforj=2,....,m we resolve the vectorv1 into its components parallel and perpendicular to the span of the preceding vectors v1,....,vj-1,

Then

u1=1||v1||v1,u2=1||v2||v2,.....,uj=1||vj||vj,.....,um=1||vm||vm

02

Apply the Gram-Schmidt process

Let the given vectors are v1=[5422],v2=[367-2].

Obtain the values of , according to the Gram-Schmidt process.

u1=v1||v||....(1)u2=v2-(u1.v2)u1||v2-(u1.v2u1||.....(2)

Find u1.

u1=152+42+22+225422=175422

03

Find u⃗2

Now, here is need to find out the values of v2-(u1.v2)u1and||v2-(u1.v2)u1||to obtain the value of u2.

Consider the equations below.

role="math" localid="1659441637408" u1v1=7u1v1u1=5423v1-u1v1u1=367-2-5422=-225-4

Then,

v1-u1v1u1=4+4+25+16=49=7

Now find role="math" localid="1659441716297" u2.

u2=17-225-4

Thus, the values of u1,u2are [5/74/72/72/7],-2/72/75/7-4/7.

Hence, the orthonormal vectors are [5/74/72/72/7],-2/72/75/7-4/7.

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Most popular questions from this chapter

Consider the linear systemAx=b , where

A=[1326]and b=[1020].

a. Draw a sketch showing the following subsets of 2:

  • The kernel ofA , and(kerA)
  • The image of AT
  • The solution setSof the system Ax=b

b.What relationship do you observe between(kerA) and im(AT)? Explain.

c. What relationship do you observe betweenrole="math" localid="1660916844921" ker(A) and S? Explain.

d. Find the unique vectorx0 in the intersection ofS and(kerA) . Show x0on your sketch.

e. What can you say about the length of x0compared with the length of all other vectors in S?

To make a trend analysis of six evenly spaced data points, one can use orthogonal polynomials with respect to evaluation at the points \(t = - 5, - 3, - 1,\,\,1,\,\,3,{\rm{ and }}5\).

  1. Show that the first three orthogonal polynomials are

\({p_0}\left( t \right) = 1,\,\,\,\,\,\,{p_1}\left( t \right) = t,{\rm{ and }}{p_2}\left( t \right) = \frac{3}{8}{t^2} - \frac{{35}}{8}\)

(The polynomial \({p_2}\) has been scaled so that its values at the evaluation points are small integers.)

  1. Fit a quadratic trend function to the data \(\left( { - 5,1} \right),\left( { - 3,1} \right),\left( { - 1,4} \right),\left( {1,4} \right),\left( {3,6} \right),\left( {5,8} \right)\).

Find the least-squares line \(y = {\beta _0} + {\beta _1}x\) that best fits the data \(\left( { - 2,0} \right),\left( { - 1,0} \right),\left( {0,2} \right),\left( {1,4} \right),{\rm{ and }}\left( {2,4} \right)\), assuming that the first and last data points are less reliable. Weight them half as much as the three interior points.

Find an orthonormal basis of the kernel of the matrix A=[11111234].

Question: In Exercises 1 and 2, you may assume that\(\left\{ {{{\bf{u}}_{\bf{1}}},...,{{\bf{u}}_{\bf{4}}}} \right\}\)is an orthogonal basis for\({\mathbb{R}^{\bf{4}}}\).

1.\({{\bf{u}}_{\bf{1}}} = \left[ {\begin{aligned}{*{20}{c}}{\bf{0}}\\{\bf{1}}\\{ - {\bf{4}}}\\{ - {\bf{1}}}\end{aligned}} \right]\),\({{\bf{u}}_{\bf{2}}} = \left[ {\begin{aligned}{*{20}{c}}{\bf{3}}\\{\bf{5}}\\{\bf{1}}\\{\bf{1}}\end{aligned}} \right]\),\({{\bf{u}}_{\bf{3}}} = \left[ {\begin{aligned}{*{20}{c}}{\bf{1}}\\{\bf{0}}\\{\bf{1}}\\{ - {\bf{4}}}\end{aligned}} \right]\),\({{\bf{u}}_{\bf{4}}} = \left[ {\begin{aligned}{*{20}{c}}{\bf{5}}\\{ - {\bf{3}}}\\{ - {\bf{1}}}\\{\bf{1}}\end{aligned}} \right]\),\({\bf{x}} = \left[ {\begin{aligned}{*{20}{c}}{{\bf{10}}}\\{ - {\bf{8}}}\\{\bf{2}}\\{\bf{0}}\end{aligned}} \right]\)

Write x as the sum of two vectors, one in\({\bf{Span}}\left\{ {{{\bf{u}}_1},{{\bf{u}}_2},{{\bf{u}}_3}} \right\}\)and the other in\({\bf{Span}}\left\{ {{{\bf{u}}_{\bf{4}}}} \right\}\).

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