Extend Vector to Orthogonal Basis

In summary, to extend a vector (1,2,3) to an orthogonal basis for R^3, you can first find a perpendicular vector, such as (-5, 1, 1) by using the dot product. Then, using the cross product, you can find a second perpendicular vector, such as (-1,-16,11). These two vectors can then be used as a basis for R^3. There may be other possible solutions as well.
  • #1
special-g
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How do you extend a vector (let's use vector (1,2,3) for example) to an orthogonal basis for R^3?
 
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  • #2
special-g said:
How do you extend a vector (let's use vector (1,2,3) for example) to an orthogonal basis for R^3?

First find a vector perpendicular to (1,2,3). That's not hard if you think about the dot product. Any one, there are many. Then find a vector perpendicular to the first two. That's easy in R^3 if you use the cross product. There is no unique answer, you know.
 
  • #3
Thanks, that helps quite a bit...we just started this material and there aren't very many examples in the book to go off of. :)

I don't know if I did this completely right because I haven't taken calc 3 in a while.

For the first vector, would this be one answer: vector (-5, 1, 1) after taking the dot product.
Then, after taking the cross product of those two vectors, I got vector (-1,-16,11).
 
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1. What is the purpose of extending a vector to an orthogonal basis?

The purpose of extending a vector to an orthogonal basis is to simplify the representation of the vector and make it easier to perform calculations involving the vector. An orthogonal basis consists of a set of vectors that are all perpendicular to each other, making it easier to determine the magnitude and direction of the original vector.

2. How do you extend a vector to an orthogonal basis?

To extend a vector to an orthogonal basis, you first need to find a set of orthogonal vectors that span the same space as the original vector. This can be done through various methods such as Gram-Schmidt process or using matrix operations. Once you have the orthogonal basis, you can then express the original vector as a linear combination of the orthogonal vectors.

3. Can any vector be extended to an orthogonal basis?

No, not all vectors can be extended to an orthogonal basis. In order for a vector to be extendable, it must be a part of a vector space that has a basis. A vector space is a collection of vectors that satisfies certain properties, and a basis is a set of vectors that can be used to represent all of the vectors in that space.

4. What are the benefits of using an orthogonal basis?

Using an orthogonal basis can make calculations involving vectors much simpler and more efficient. It also allows for easier visualization of vector operations and can help with understanding the relationships between vectors. Additionally, using an orthogonal basis can help reduce errors in calculations and make it easier to check for mistakes.

5. Can extending a vector to an orthogonal basis change its properties?

Yes, extending a vector to an orthogonal basis can change some of its properties. For example, the length of the vector may change since it is now represented as a linear combination of orthogonal vectors. However, some properties such as direction and span will remain the same since the original vector and the orthogonal vectors span the same space.

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