Finding Orthonormal Set q1, q2, q3 for Column Space of A

In summary, the problem is to find an orthonormal set q1, q2, q3 for which q1, q2 span the column space of A. The given matrix A has two linearly independent columns, but they are not orthogonal. The Gram-Schmidt method can be used to find an orthonormal basis. Alternatively, the vector cross product can be used if A is in R3. It is important to note that orthogonal vectors are always independent, but independent vectors may not be orthogonal.
  • #1
EvLer
458
0
I just need a hint.
Problem:
find an orthonormal set q1, q2, q3 for which q1, q2 span the column space of A, where
A =
[1 1]
[2 -1]
[-2 4]

of course I should apply the Gram-Schmidt method, but the problem is that the column vectors are not independent and Gram-Schmidt starts with independent vectors. I can arrive at independent columns by Gaussian elimination that would span the subspace of the column space, so is that what I should use for finding orthonormal qs?
Thanks.
 
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  • #2
The two columns look independent to me.
 
  • #3
but if I take inner product i don't end up with 0...
 
  • #4
EvLer said:
but if I take inner product i don't end up with 0...
Then they aren't orthogonal.
 
  • #5
EvLer said:
but if I take inner product i don't end up with 0...

Of course they aren't! You are asked to find an orthonormal basis. You would hardly expect them to give you vectors that are already orthogonal!

The two vectors you are given definitely are independent- the only way two vectors can be dependent is if one is a multiple of the other and that clearly is not the case here.

Apply "Gram-Schmidt" to them!
 
  • #6
Since A is 2x3, you can also use a trick that works in R3 only. The vector cross product is very useful for constructing an orthonormal set.
 
  • #7
oh, ok, I know where I got confused: othogonal is always independent, independent may not be orthogonal... thanks
 

1. What is an orthonormal set?

An orthonormal set is a set of vectors that are all mutually perpendicular to each other, and have a length of 1. This means that the dot product of any two vectors in the set is equal to 0, and the length of each vector is equal to 1.

2. Why is it important to find an orthonormal set for the column space of a matrix?

Finding an orthonormal set for the column space of a matrix can help simplify calculations and make it easier to work with the data contained in the matrix. It also allows for a more efficient and accurate representation of the data.

3. How do you find an orthonormal set for the column space of a matrix?

To find an orthonormal set for the column space of a matrix, you can use the Gram-Schmidt process. This involves finding a set of vectors that are orthogonal to each other, and then normalizing each vector to have a length of 1. This process is repeated until you have an orthonormal set for the column space.

4. What is the significance of an orthonormal basis for a vector space?

An orthonormal basis is a set of vectors that forms a basis for a vector space and is also orthonormal. This means that the basis vectors are mutually perpendicular and have a length of 1. Having an orthonormal basis is important because it simplifies calculations and makes it easier to represent vectors in the vector space.

5. Are there any real-world applications for finding an orthonormal set for the column space of a matrix?

Yes, there are many real-world applications for finding an orthonormal set for the column space of a matrix. Some examples include data compression, image processing, and solving systems of equations. In these applications, having an orthonormal set allows for more efficient and accurate calculations and representations of the data.

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