What is the basis for W perp in the Gram Schmidt process?

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In summary, the problem asked to find an orthogonal basis for a subspace W and a basis for its orthogonal complement, W perp. After applying the Gram Schmidt process, a basis for W was found to be {[1; -4; 0; 1], [5; 1; -4; -1]}. To find a basis for W perp, the transpose of W was taken and row-reduced, resulting in the parametric equations x3 = 21 and x4 = 7. Using these values, two vectors were found to be orthogonal to W, {[16; 4; 21; 0], [1; 2; 0; 7]}. While this is not the
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Homework Statement



Let W be a subspace of ℝ4 spanned by the vectors:

u1 = [1; -4; 0; 1], u2 = [7; -7; -4; 1]

Find an orthogonal basis for W by performing the Gram Schmidt proces to there vectors. Find a basis for W perp (W with the upside down T).


Homework Equations



Gram Schmidt

The Attempt at a Solution



I applied the Gram Schmidt process and found the basis for W which was {[1; -4; 0; 1], [5; 1; -4; -1].

Here's where I run into the problem. I'm trying to get the basis for W perp, but I don't really know what to do. I tried finding the basis for the transpose of W, I got x3 and x4 as the free variables, but the resulting vectors I got was wrong, where do I start from here?

Thanks.
 
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  • #2
I did the same thing and got the same free variables. Those are the correct variables. Are you sure you are getting the wrong vectors? Which ones are you getting?
 
  • #3
I'm getting x3[0; 4/21; 1; 0] and x4[-1; 6/21; 0; 1], but the answer is [4; 0; 6; -4], [0; 4; -3; 16]. I've done the calculation several times and I keep getting the same answers.

EDIT:

I got to those vectors by transposing W, resulting in:

[1, -4, 0, 1; 5 1 -4 -1]. After that I row reduced it and got my parametric equations.
 
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  • #4
What is your row-reduced matrix? It looks like you might be making a mistake there.
I might suggest putting this into wolfam|alpha and seeing if you are messing up you row-reductions any. Also, forget about what the book says the basis should be. I have found that in problems like this, book authors often put a technically correct answer in the back of the book, but perhaps not one that you would normally get. So, to check your answers, just take the dot product of the vectors you get with each of the vectors you were given. They should all be zero, right?
 
  • #5
Plugging in [1, -4, 0, 1; 5 1 -4 -1] in wolfram|alpha and having it row reduce the matrix gave me [1, 0, -16/21, -1/7; 0 1 -4/21, -2/7].

Doing the calculations again I get the free variables x3 and x4 with x3[16/21; 4/21; 1; 0] and x4[1/7; 2/7; 0; 1].

Scaling these vectors doesn't get me anywhere near [4; 0; 6; -4], [0; 4; -3; 16]. I suspect that I'm working with the wrong vectors while solving for the parametric equations, but I can't think of what other vectors I can use.
 
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  • #6
OK, to make calculations simple, let x3 = 21 and x4 = 7. Then your two vectors are:

[16 4 21 0] and [1 2 0 7]

if I did my arithmetic correctly, both of these are orthogonal to both of the vectors you were given. So, these span W perp. Now, you were asked for A basis in the problem right? That is, not THE basis. The answer in the back of the book is also A basis for W perp, just not the same as the one you got. Your answer is correct. To convince yourself, show that the two vectors given in the book are in the linear span of the two vectors you computed.
 
  • #7
Is my basis different because there are infinitely many solutions for this problem and I just happened to find another one? Thanks, for all the help by the way!

EDIT:

To show if the two vectors are in the linear span of the two vectors do I just take:

c1[16; 4; 21; 0] + c2 [1; 2; 0; 7] = [1; -4; 0; 1]

c1[16; 4; 21; 0] + c2 [1; 2; 0; 7] = [-7; -7; -4; 1]

and solve for c1 and c2?
 
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  • #8
Yes to both questions.

I'm not really sure how whoever wrote the solutions came up with that particular basis. I'd have to guess that he did it exactly the way we did it, and then took some odd linear combinations to come up with what is in the back of the book. Anyway, on problems like this, I wouldn't even look at the back of the book because it is really easy to check by yourself anyway. And, as you correctly pointed out, there are infinite solutions to this problem.
 

What is the basis for W perp?

The basis for W perp is the set of vectors that are orthogonal (perpendicular) to all vectors in W. In other words, it is the set of all vectors that form a right angle with every vector in W.

How do you find the basis for W perp?

To find the basis for W perp, you can use the Gram-Schmidt process. This involves taking the vectors in W and constructing a new set of vectors that are orthogonal to each other. The resulting set of vectors will be the basis for W perp.

Why is finding the basis for W perp important?

Finding the basis for W perp is important because it allows us to decompose a vector space into two orthogonal subspaces. This can be helpful in solving problems in linear algebra, such as finding the projection of a vector onto a subspace.

Can the basis for W perp be empty?

Yes, it is possible for the basis for W perp to be empty. This means that there are no vectors that are orthogonal to all vectors in W. In other words, W is already a subspace of the vector space and there is no need for an orthogonal complement.

What is the relationship between the basis for W perp and the null space of the transpose of the matrix representing W?

The basis for W perp is equivalent to the basis for the null space of the transpose of the matrix representing W. This is because the null space of a matrix is the set of all vectors that are orthogonal to the columns of the matrix. So, the basis for W perp and the basis for the null space of the transpose of the matrix are both sets of vectors that are orthogonal to the same set of vectors (the columns of the matrix representing W).

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