Finding the Projection of a Vector onto a Subspace

In summary, the conversation is about finding the projection of a vector x onto a subspace S in R^3. The suggested method is to find an orthogonal or orthonormal basis for S and then project x onto each basis vector individually. Alternatively, one can think of S as representing a plane in R^3 and find the projection of x onto that plane.
  • #1
Dustinsfl
2,281
5
Let S be a subspace of R3 spanned by u2=[tex]\left[ \begin{array} {c}
\frac{2}{3} \\
\frac{2}{3} \\
\frac{1}{3} \end{array} \right][/tex] and u3=[tex]\left[ \begin{array} {c}
\frac{1}{\sqrt{2}} \\
\frac{-1}{\sqrt{2}} \\
0 \end{array} \right][/tex].
Let x=[tex]\left[ \begin{array} {c}
1 \\
2 \\
2 \end{array} \right][/tex]. Find the projection of p of x onto S.

I know how to find projection but I am not sure about doing the projection on a subspace.
 
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  • #2
how about finding an orthogonal basis of S (orthonormal is even better), then the projection of x onto each basis vector...?
 
  • #3
or equivalently, S represents a plane in [itex]\mathbb{R}^3[/itex], so find the projection of X on that plane...
 

FAQ: Finding the Projection of a Vector onto a Subspace

What is projection on a subspace?

Projection on a subspace is a mathematical operation that involves finding the closest point on a subspace to a given vector. In other words, it is the process of finding the component of a vector that lies in a specific subspace.

What is the purpose of projection on a subspace?

The purpose of projection on a subspace is to simplify a complex problem by breaking it down into smaller, more manageable parts. It is often used in linear algebra and other areas of mathematics to solve optimization problems and to find the best fit for data.

How is projection on a subspace calculated?

To calculate projection on a subspace, we use the dot product or inner product between the vector and the basis vectors of the subspace. This produces a scalar quantity that represents the magnitude of the projection. The projection vector is then obtained by multiplying this scalar by the basis vector.

What is the difference between orthogonal and non-orthogonal projection on a subspace?

Orthogonal projection on a subspace involves finding the component of a vector that is perpendicular to the subspace, while non-orthogonal projection involves finding the component that is not necessarily perpendicular to the subspace. Orthogonal projection is often preferred as it simplifies the calculation and produces a unique solution.

How is projection on a subspace used in real-world applications?

Projection on a subspace has many practical applications, such as in data compression, image processing, and machine learning. It is also used in physics and engineering to model and solve various problems. Additionally, it is used in computer graphics to create 3D projections of objects onto a 2D screen.

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