Basis vectors and ortho solution spaces

In summary, the conversation discusses finding a basis for two homogenous equations and how to derive the basis vectors. The solution vector x is a solution if it is orthogonal to the row vectors, which can be used as a basis for the space orthogonal to x. Different methods can be used to find the basis vectors, resulting in different solutions.
  • #1
EWW
9
0
Hello,

I've got two homogenous equations: 3x + 2y + z - u = 0 and 2x + y + z +5u = 0. I'm trying to find a basis for these solutions. The solution vector x [x, y, z, u] is a solution if and only if it is orthogonal to the row vectors, in this case a and b ([3, 2, 1, -1], [2, 1, 1, 5)]. My understanding is that these row vectors span the space orthogonal to x, and they thus can be used as a basis. The answer given by the text I'm using gives for a basis these two vectors [1, -1, -1, 0] and [0, 6, -11, 1]. How were these basis vectors derived? I tried doing a linear combination of a and b to get the textbook answer but I couldn't get that to work. Help!

EWW
 
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  • #2
I get a different basis, namely [-1, 1, 1, 0] and [-11, 17, 0, 1], but your vectors also are a basis for the solution space defined by the two equations.

How did I get mine? I row reduced the 2 X 4 matrix whose rows were the coefficients of x, y, z, and u.

I ended up with
[1 0 1 11]
[0 1 -1 -17]

Call the reduced matrix A. Then A [x y z u]^T = 0
From this you get [x y z u]^T = z[-1 1 1 0]^T + u[-11 17 0 1]^T

The solution space is the 2-D subspace of R^4 spanned by/made up of linear combinations of the vectors you show or the vectors I show. The solution space is a hyperplane in R^4. Any two vectors that aren't parallel and that lie in this hyperplane would make a basis.

Mark
 
  • #3
EWW said:
My understanding is that these row vectors span the space orthogonal to x, and they thus can be used as a basis.

Hello EWW! :smile:

You're getting confused …

they can't be used as a basis for a space they are orthogonal to. :wink:
 
  • #4
As tiny-tim said, you are confusing the "solution space" and the space orthogonal to the solutions space. Any linear combination of a and b will be orthogonal to the solution space, not in the solution space.

EWW here's how I would do the problem: The solution space consists of vectors <x, y, z, u> satisfying 3x + 2y + z - u = 0 and 2x + y + z +5u = 0. Subtract the second equation from the first to eliminate z: x+ y- 6u= 0 so x= -y+ 6u. Put that back into the first equation: 3(-y+ 6u)+ 2y+ z- u= -y+ 17u+ z= 0 so z= y- 17u. Take y= 1, u= 0. Then x= -1 and z= 1. <-1, 1, 0, 1> is in the solution set. Take y= 0, u= 1. Then x= 6 and z= -17. <6, 0, -17, 1> is also in the solution set and the two vectors form a basis.

If, instead, I had solved the equation x+ y- 6u= 0 for y, y= -x+ 6u, and put that back into the first equation I would have got z= -x-11u so that I have y and z in terms of x and u. Taking x= 1, u= 0 gives <1, -1, -1, 0> and taking x= 0, u= 1 gives <0, 6, -11, 1> the solution in your textbook.

If you were to solve for x and y in terms of z and u, then take z=1, u=0 and z=0, u= 1, you would get Mark44's solution.
 

FAQ: Basis vectors and ortho solution spaces

What are basis vectors?

Basis vectors are a set of linearly independent vectors that can be used to represent any other vector in a vector space through a linear combination.

How are basis vectors chosen?

Basis vectors are chosen in a way that they are linearly independent and span the entire vector space. This means that any vector in the vector space can be expressed as a unique linear combination of the basis vectors.

What is an ortho solution space?

An ortho solution space is a set of vectors that are orthogonal (perpendicular) to each other and also span the space. Orthogonal vectors have a dot product of 0, meaning they are at a right angle to each other.

How is an ortho solution space related to basis vectors?

An ortho solution space can be created using basis vectors that are orthogonal to each other. The basis vectors form a basis for the space and the orthogonal vectors form an orthogonal basis for the space.

Why are basis vectors and ortho solution spaces important in linear algebra?

Basis vectors and ortho solution spaces are important because they allow for efficient representation and manipulation of vectors and matrices in linear algebra. They also provide a way to solve systems of linear equations and find solutions in a more intuitive and systematic manner.

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