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Finding an orthonormal basis |
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| Nov13-08, 09:41 PM | #1 |
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Finding an orthonormal basis
1. The problem statement, all variables and given/known data
Find an orthonormal basis for the subspace of R^3 consisting of all vectors (a, b, c) such that a + b + c = 0. 2. Relevant equations 3. The attempt at a solution I know how to find an orthonormal basis just for R^3 by taking the standard basis vectors (1, 0, 0), (0, 1, 0), and (0, 0, 1) and applying the Gram-Schmidt process to make them orthonormal. The condition that a + b + c must equal 0 is throwing me off, however. Can anyone give me any suggestions for how to approach problems like these? thanks! |
| Nov13-08, 10:02 PM | #2 |
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If you know Gram-Schmidt, that's the hard part. What's so hard about about finding two vectors (a,b,c) such that a+b+c=0 to do Gram-Schmidt with? (1,-1,0) sounds like a good start. Give me another one.
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| Nov13-08, 10:07 PM | #3 |
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I think I need 3 vectors, right? such that a + b + c = 0. Can I start with any vector? Or is there a reason why (1, -1, 0) is a good choice? If it can be any 3 vectors that add to 0 it should be simpler, but then I can't be sure they are a basis?
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| Nov13-08, 10:10 PM | #4 |
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Finding an orthonormal basis
Why do you need 3 vectors? That's a subspace of R^3. It looks to me like it's two dimensional.
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| Nov13-08, 10:16 PM | #5 |
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Ohh.. sorry I was being confused, I thought a, b, and c referred to vectors and not the components.
So I can choose (1, -1, 0) like you said and also (1, 0, -1)? I would still have to check if the 2 vectors I choose are actually a basis (span R^3 and are linearly independent) right? |
| Nov13-08, 10:18 PM | #6 |
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Sure, exactly. That's a good choice. There aren't too many dumb choices. (1,-1,0) and (-1,1,0) would have been a dumb choice because they're linearly dependent. But you didn't make the dumb choice. Now do Gram-Schmidt.
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| Nov13-08, 11:57 PM | #7 |
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Mentor
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| Nov14-08, 12:13 AM | #8 |
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a + b + c = 0 If you solve for a, you get Code:
a = -b - c, where b and c are arbitrary b = b c = c To make things even more explicit, Code:
a = -1b - 1c b = 1b + 0c c = 0b +1 c [tex] \left[ \begin{array}{ c } a \\ b \\ c \end{array} \right] = b\left[ \begin{array}{ c } -1 \\ 1 \\ 0 \end{array} \right] + c\left[ \begin{array}{ c } -1 \\ 0 \\ 1 \end{array} \right][/tex] Voila, there's your basis. |
| Nov14-08, 04:17 AM | #9 |
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| Jul27-10, 12:09 AM | #10 |
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I'm currently doing the same problem so I figured I'd revive this old thread.
Once I have my two vectors, u1=<-1,1,0> and u2=<-1,0,1> I then go through the Gram-Schmidt process to find the normalized basis? |
| Jul27-10, 01:08 AM | #11 |
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If you already have a basis, you don't need Gram-Schmidt to find a normalized basis.
Do you know what the term "normalized" means? |
| Jul27-10, 01:15 AM | #12 |
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| Jul27-10, 02:15 PM | #13 |
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OK, in that case you need to use G-S.
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