Projecting vectors from R3 onto a subspace

In summary, the conversation discusses finding the vector projection of a given vector onto a subspace in R3. The formula for vector projection is given as p = (<u,v>/<v,v>)*v, where u is the vector to be projected and v is the basis for the subspace. The conversation also touches on finding the projection matrix for vectors in R3 onto the orthogonal complement of a two-dimensional subspace, using the same formula. The resulting projection matrix is P = [(-2/9)(-2x +2y +z)] [ (2/9)(-2x +2y +z) ] [ (1/9)(-2x +2y +z) ].
  • #1
Ghost of Progress
5
0
I want to project a vector from R3 onto a subspace.
I'll let the bases for the subspace be [a,b,c]T
(my T's mean transpose)
---
I have the defintion for vector projection
p = (<u,v>/<v,v>)*v
---
I know v will be the [a,b,c]T vector but what is u?
The only thing I could think of is let it be the triplet [x,y,z]T which could be any vector in R3.
---
Using this I get
p = [(a/(a^2 + b^2 + c^2))(ax + by + cz)]
[(b/(a^2 + b^2 + c^2))(ax + by + cz)]
[(c/(a^2 + b^2 + c^2))(ax + by + cz)]
---
I'm not very confident with this solution, I was hoping someone could tell me if this is correct or show me where I've gone wrong.
 
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  • #2
u is presumably the vector you want to project onto the subspace.
 
  • #3
I was just working an a problem that askes me to find the projection matrix P that projects vectors in R3 onto the orthoginal compliment of a two dimensional subsapce of R3 spanned by
x1 = [1,0,2]T x2 = [0,1,-2]
---
I've found that the bases of the orthoginal compliment is [-2,2,1]T
---
Using the defintion of P that a posted above I've found
P = [(-2/9)(-2x +2y +z)]
[ (2/9)(-2x +2y +z) ]
[ (1/9)(-2x +2y +z) ]

where, like you said, u = (x,y,z) = the vector I want to project onto the subspace. Does this seem like a correct solution?
 

1. What is the purpose of projecting vectors from R3 onto a subspace?

The purpose of projecting vectors from R3 onto a subspace is to find the closest vector in the subspace to the given vector in R3. This can help with simplifying calculations and finding solutions in a more manageable subspace.

2. How do you project a vector from R3 onto a subspace?

To project a vector from R3 onto a subspace, you can use the formula projU(v) = ((v ⋅ u1)/||u1||2)u1 + ... + ((v ⋅ un)/||un||2)un, where u1, ..., un are the basis vectors for the subspace.

3. What is the difference between an orthogonal projection and a non-orthogonal projection?

An orthogonal projection is a projection onto a subspace where the basis vectors are all perpendicular to each other, while a non-orthogonal projection is a projection onto a subspace where the basis vectors are not necessarily perpendicular to each other. In other words, an orthogonal projection preserves the angle between the original vector and the projected vector, while a non-orthogonal projection does not necessarily preserve this angle.

4. Can you project vectors from R3 onto a subspace with a different dimension?

Yes, you can project vectors from R3 onto a subspace with a different dimension. However, the projected vector will not lie entirely in the subspace, as it will have components in the directions of the extra dimensions.

5. What are some practical applications of projecting vectors from R3 onto a subspace?

Projecting vectors from R3 onto a subspace has many practical applications in fields such as computer graphics, physics, and engineering. For example, in computer graphics, projecting points onto a 2D plane can help with creating 3D images, and in physics, projecting vectors onto a coordinate system can simplify calculations. It can also be used in data analysis to reduce the dimensionality of a dataset and make it easier to interpret.

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