Creating a Unit Vector after Gram Schmidt Process?

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In summary, the G-S algorithm produces two vectors, the first of which is perpendicular to the second; the second is just multiplied by $1/\sqrt{5}$. If one of the vectors is 0, it means the corresponding original vector belongs to the span of the previous vectors.
  • #1
bugatti79
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Folks,

Where am I going wrong?

[tex]v_1=(3,0,0)[/tex], [tex]v_2=(0,1,2)[/tex],[tex]v_3=(0,2,5)[/tex]

[tex]u_1=(3,0,0)[/tex]

[tex]u_2=(0,1,2)-\frac{(0,1,2)(3,0,0)}{||(3,0,0)||^2}(3,0,0)[/tex]

The inner product (0,1,2)(3,0,0) yields 0...?
 
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  • #2
bugatti79 said:
The inner product (0,1,2)(3,0,0) yields 0...?
So what?
 
  • #4
bugatti79 said:
Inner product of those 2 equal to 0 would suggest they are perpendicular
Yes.

bugatti79 said:
but according to wolfram
Again, so what? (Smile) The second vector in W|A results is collinear with the original second vector; it is just multiplied by $1/\sqrt{5}$ so that its length becomes 1. The first vector is also normalized.

Addition: If, on the other hand, one of the vectors produced by the algorithm is 0, it means that the corresponding original vector belongs to the span of the previous vectors. Such vector can be simply omitted.
 
  • #5
Evgeny.Makarov said:
Yes.

Again, so what? (Smile) The second vector in W|A results is collinear with the original second vector; it is just multiplied by $1/\sqrt{5}$ so that its length becomes 1. The first vector is also normalized.

Addition: If, on the other hand, one of the vectors produced by the algorithm is 0, it means that the corresponding original vector belongs to the span of the previous vectors. Such vector can be simply omitted.

ok, I calculate

[tex]u_3=v_3-\frac{(v_3,u_1)}{||u_1||^2} u_1-\frac{(v_3,u_2)}{||u_2||^2}u_2[/tex]

[tex]=(0,2,5)-0-\frac{12}{5}(0,1,2)=(0,-2/5,1/5)[/tex]

I don't know where the sqrt is coming from? ie, [tex]||u_2||^2=(0^2+1^2+2^2)=5[/tex]...?
 
  • #6
bugatti79 said:
I don't know where the sqrt is coming from? ie, [tex]||u_2||^2=(0^2+1^2+2^2)=5[/tex]...?
Could you formulate your questions more precisely? I suppose you are asking about the square root in the W|A results; you should say so. And how exactly does the fact that [tex]\|u_2\|^2=5[/tex] contradict that?

The norm of $u_3$ is
\[
\left\|\left(0,-\frac25,\frac15\right)\right\|=\sqrt{\left(-\frac25\right)^2+\left(\frac15\right)^2}=\sqrt{\frac{4}{25}+\frac{1}{25}}=\sqrt{\frac{5}{25}}=\sqrt{\frac15}.
\]
The unit vector is
\[
\frac{u_3}{\|u_3\|}=\frac{u_3}{\sqrt{1/5}}=\sqrt{5}u_3=\left(0,-\frac{2}{\sqrt{5}},\frac{1}{\sqrt{5}}\right).
\]
 
  • #7
Evgeny.Makarov said:
Could you formulate your questions more precisely? I suppose you are asking about the square root in the W|A results; you should say so. And how exactly does the fact that [tex]\|u_2\|^2=5[/tex] contradict that?

The norm of $u_3$ is
\[
\left\|\left(0,-\frac25,\frac15\right)\right\|=\sqrt{\left(-\frac25\right)^2+\left(\frac15\right)^2}=\sqrt{\frac{4}{25}+\frac{1}{25}}=\sqrt{\frac{5}{25}}=\sqrt{\frac15}.
\]
The unit vector is
\[
\frac{u_3}{\|u_3\|}=\frac{u_3}{\sqrt{1/5}}=\sqrt{5}u_3=\left(0,-\frac{2}{\sqrt{5}},\frac{1}{\sqrt{5}}\right).
\]

Ah yes, one still has to create the unit vector after the G-S process is performed.
Ok, I see it now. Thanks very much for your time.
 

FAQ: Creating a Unit Vector after Gram Schmidt Process?

What is Gram Schmidt in 3 space?

Gram Schmidt in 3 space is a mathematical algorithm used to find an orthogonal basis for a given set of vectors in three-dimensional space.

What is the purpose of Gram Schmidt in 3 space?

The purpose of Gram Schmidt in 3 space is to simplify vector calculations and make it easier to work with linearly independent vectors.

How does Gram Schmidt in 3 space work?

Gram Schmidt in 3 space works by taking a set of vectors and systematically transforming them into a new set of orthogonal vectors using a series of calculations and projections.

What are the benefits of using Gram Schmidt in 3 space?

Using Gram Schmidt in 3 space allows for easier manipulation of linearly independent vectors and can help with solving problems involving vector spaces and linear transformations.

Are there any limitations to using Gram Schmidt in 3 space?

While Gram Schmidt in 3 space is a useful tool, it does have limitations. It may not work for non-linearly independent vectors and can be computationally expensive for larger sets of vectors.

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