The approach to project out certain vector

In summary, the best way to project out the v component from a vector u is to use the Gram-Schmidt process of orthonormalization. This involves updating v by subtracting the projection of u onto v, which can be calculated using the inner product. Normalization is not strictly necessary for having a basis, but it is recommended for obtaining an orthonormal basis.
  • #1
onako
86
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Given that certain nullspace is spanned by a vector v, what would be the procedure to project out the v component from certain vector u? Perhaps with the Gram-Schmidt process of orthonormalization by updating
v = v - proj(u, v)

where proj(u, v) = (<u, v>/<u, u>)u, and <u, v> denotes the inner product? If that is correct way to do it, please let me know. However, if there are alternatives, I would be happy to consider those.
 
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  • #2
Hey onako.

Yes, you're right on the money with using Gram-Schmidt process which basically does exactly what you are trying to do by 'projecting out' all of the components that have been calculated that correspond to elements of your new orthonormal basis.

Basically it boils down to thinking about the projection really is and this boils down to standard vector geometry definitions.

We know from Gram-Schmidt that if we have a vector v with u as our chosen first component of our new basis, then we do what you have said in your formula above. It is the best way to do this and it is the standard way to attack these kinds of problems.

The only thing I wanted to add was that if you need an orthonormal basis, just be aware to normalize but this is not a strict requirement for having a basis.
 
  • #3
Thanks. Indeed, I'll need a normalization; good that you pointed that out.
 

Related to The approach to project out certain vector

1. What is the meaning of "projecting out a vector" in a project approach?

"Projecting out a vector" refers to the process of removing or eliminating a specific vector or component from a larger set of data or information. This can be done in various fields, such as mathematics, physics, and computer science, as a way to simplify and focus on specific aspects of a project.

2. Why is it important to project out certain vectors in a project?

Projecting out certain vectors allows for a more focused and streamlined approach to a project. By removing unnecessary or irrelevant components, it can help to simplify complex problems and make them more manageable to solve. It can also lead to more accurate and precise results.

3. What are the different methods for projecting out vectors in a project?

There are several methods for projecting out vectors, including orthogonal projection, oblique projection, and Gram-Schmidt process. These methods vary in complexity and suitability for different types of projects, so it is important to determine the most appropriate method for a specific project.

4. Can projecting out vectors affect the outcome of a project?

Yes, projecting out vectors can significantly impact the outcome of a project. By removing certain components, it can change the focus and direction of the project, leading to different results. It is important to carefully consider the implications of projecting out vectors before implementing it in a project.

5. Are there any limitations to projecting out vectors in a project?

While projecting out vectors can be a useful tool in project approaches, it is not always applicable or feasible. For example, in some cases, removing certain vectors may result in losing important information or data that is necessary for the project. Additionally, the process of projecting out vectors can be time-consuming and may require advanced mathematical or technical knowledge.

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