Find Basis for Uperp from x1, x2, x3: Orthogonal Bases

In summary: For the first coordinate, you have -(-14/77)-242/77=14/77-242/77=-228/77For the other coordinates, you have -[-2/11 6/11 -2/11 0] - [22/7 11/7 11/7 11/7]So, the two solutions are the same except for the first coordinate.
  • #1
theRukus
49
0

Homework Statement


Let U be a subspace of R4 and let S={x1, x2, x3} be an orthogonal basis of U.

Given x1, x2, x3, find a basis for Uperp (the subspace containing all vectors orthogonal to all vectors in U).

I am actually given three vectors x1, x2, x3, but I am looking more to understand the concept.


Homework Equations





The Attempt at a Solution


Since all vectors in Uperp are orthogonal all vectors in U, I am led to believe that all vectors in a basis of Uperp would be orthogonal to the vectors in the basis of U... But the vectors I am given are all orthogonal to one another, so I am somewhat confused.

Any insight is appreciated. Thank you.
 
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  • #2
theRukus said:
Since all vectors in Uperp are orthogonal all vectors in U, I am led to believe that all vectors in a basis of Uperp would be orthogonal to the vectors in the basis of U... But the vectors I am given are all orthogonal to one another, so I am somewhat confused.

Given that [tex]\dim U = 3[/tex] and you are working in [tex]\mathbb{R}^4[/tex], what do you expect the dimension of [tex]U^\perp[/tex] to be? (Just because [tex]x_1, x_2, x_3[/tex] are all mutually orthogonal, that doesn't necessarily mean you can't have another vector orthogonal to all of them.)
 
  • #3
Yes, given. However, wouldn't the basis for [tex]U^\perp[/tex] have to consist of 3 new vectors, each orthogonal to [tex]x_1, x_2, x_3[/tex]?
 
  • #4
No, the basis of [tex]U^\bot[/tex] will not consist of three vectors. It will consist of one vector, which is orthogonal to the basis in U.
 
  • #5
Thank you
 
Last edited:
  • #6
Alright. I have been trying to solve in the following manner:

Pick a random vector x.

Solve for z = x - projx1(x) - projx2(x) - projx3(x)

That is, z equals the random vector x minus x's projections on the three orthogonal vectors.

This should leave me with one vector z orthogonal to all three original vectors, correct?

I have tried this with three random vectors x, and for some reason every z is orthogonal to x1 and x2, but not x3. I have been redoing my calculations repeatedly, but the same thing occurs. Is this possible, or have I some error?
 
  • #7
Yes you should get to the correct answer this way (provided that the vector x is linearly independent from [tex]x_1,x_2,x_3[/tex].
If you can't find your mistake, then you can always post your work here. So we can see what went wrong...
 
  • #8
I tried again, instead using the formula

z = x - projx1(x) - projx3(x) - projx2(x)

Using this method, z is orthogonal to x1 and x3, but not x2.. What givesss...?
 
Last edited:
  • #9
The latest effort:

GIVEN: x1 = [1 0 -1 -1] x2 = [2 1 1 1] x3 = [-1 3 -1 0]

Let x = [1 2 3 4] (I have also tried with x = [1 1 1 1] and x = [2 1 2 1])
z = x - projx1(x) - projx3(x) - projx2(x)

= [1 2 3 4] - (-6/3)[1 0 -1 -1] - (2/11)[-1 3 -1 0] - (11/7)[2 1 1 1]

= [1 2 3 4] - [-2 0 2 2] - [-2/11 6/11 -2/11 0] - [22/7 11/7 11/7 11/7]

= [3 2 1 2] - [-14/77 42/77 -14/77 0] - [242/77 121/77 121/77 121/77]

=[231/77 154/77 77/77 154/77] - [-256/77 -79/77 -135/77 -121/77]

= [487 233 212 275]This vector is orthogonal to x1 and x3 but not x2 (dot product test)
 
  • #10
theRukus said:
[3 2 1 2] - [-14/77 42/77 -14/77 0] - [242/77 121/77 121/77 121/77]

=[231/77 154/77 77/77 154/77] - [-256/77 -79/77 -135/77 -121/77]

It seems that you made some sign errors in this step...
 
  • #11
I don't mean to question your authority, but I don't see any sign errors. Are you sure they're there?
 
  • #12
Well, for me we have

[3 2 1 2] - [-14/77 42/77 -14/77 0] - [242/77 121/77 121/77 121/77]
= [3 2 1 2] - ([-14/77 42/77 -14/77 0] + [242/77 121/77 121/77 121/77])
= [231/77 154/77 77/77 154/77]-[228/77 163/77 107/77 121/77]

This is a bit different then your solution:
[231/77 154/77 77/77 154/77] - [-256/77 -79/77 -135/77 -121/77]
 
  • #13
I'm at a loss to understand how the two are different. I'm comparing it to simple arithmetic:

-3 - 2 - 1 = - 3 - (2 + 1)
LS = -6, RS = -6
...

So how is this any different?

I can see that you are right; my homework problem is solved.. But now I am completely confused.
 
  • #14
Well, for the first coordinate, you have

[tex]-(-14/77)-242/77=14/77-242/77=-228/77[/tex]

thesame with the other coordinates...
 

Related to Find Basis for Uperp from x1, x2, x3: Orthogonal Bases

1. What is the purpose of finding the basis for Uperp from x1, x2, x3?

The goal of finding the basis for Uperp from x1, x2, x3 is to determine a set of vectors that are orthogonal to the given vectors x1, x2, and x3. This basis can be used to find the orthogonal complement of the subspace spanned by x1, x2, and x3.

2. How do you find the basis for Uperp from x1, x2, x3?

To find the basis for Uperp, you can use the Gram-Schmidt process. This involves taking the given vectors x1, x2, and x3 and finding a set of orthogonal vectors that span the same subspace as x1, x2, and x3. These orthogonal vectors will form the basis for Uperp.

3. Can the basis for Uperp be found without using the Gram-Schmidt process?

Yes, there are other methods for finding the basis for Uperp. One alternative method is to use the null space of the matrix formed by the given vectors x1, x2, and x3. The basis for Uperp can also be found by using the orthogonal projection matrix.

4. How is the basis for Uperp related to the span of x1, x2, and x3?

The basis for Uperp is composed of vectors that are orthogonal to the given vectors x1, x2, and x3. This means that the basis for Uperp is perpendicular to the subspace spanned by x1, x2, and x3. In other words, the basis for Uperp is the basis for the orthogonal complement of the subspace spanned by x1, x2, and x3.

5. Can the basis for Uperp be used for any subspace?

The basis for Uperp is specifically used for finding the orthogonal complement of the subspace spanned by x1, x2, and x3. Therefore, it cannot be used for any subspace. However, the concept of finding orthogonal bases can be applied to other subspaces and vector spaces.

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