Find the orthonormal basis

In summary, you can use a modified version of the Gram-Schmidt process to transform the basis S into an orthonormal basis T for R3.
  • #1
La_Lune
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Homework Statement



Consider R3 together with the standard inner product. Let A =
1 1 −1
2 1 3
1 2 −6

(a) Use the Gram-Schmidt process to find an orthonormal basis S1 for null(A), and an orthonormal basis
S2 for col(A).

(b) Note that S = S1 ∪ S2 is a basis for R3. Use the the Gram-Schmidt process to transform S into an orthonormal basis T for R3


Homework Equations


Wi=(1/||Vi||)Vi


The Attempt at a Solution


I think I know how to do the first part, but for part b the computation seems to get a bit messy so I doubt I might got the first part wrong...So after finding out the basis for S, do you just follow the regular process of Gram-Schmidt to find the orthonormal basis for R3?

Thanks!
 
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  • #2




For part b, you are correct in using the Gram-Schmidt process to transform the basis S into an orthonormal basis for R3. However, instead of using the regular process, you can use a modified version of the Gram-Schmidt process specifically for creating an orthonormal basis.

To do this, follow these steps:

1. Start with the first vector in S, let's call it v1. Normalize it by dividing it by its length ||v1|| to get w1.

2. For the next vector in S, v2, subtract the projection of v2 onto w1 from v2. This will give you a vector perpendicular to w1. Normalize this vector to get w2.

3. For the third vector in S, v3, subtract the projection of v3 onto both w1 and w2 from v3. This will give you a vector perpendicular to both w1 and w2. Normalize this vector to get w3.

4. Your orthonormal basis T will be {w1, w2, w3}.

This modified process will ensure that each vector in T is perpendicular to all the previous vectors, creating an orthonormal basis for R3. I hope this helps! Let me know if you have any further questions.
 

1. What is an orthonormal basis?

An orthonormal basis is a set of vectors in a vector space that are all unit vectors (length of 1) and are mutually orthogonal (perpendicular to each other). This means that the dot product of any two vectors in the set is equal to 0.

2. Why is finding an orthonormal basis important?

Finding an orthonormal basis is important in many areas of mathematics and science, particularly in linear algebra and signal processing. It allows for easier calculations and simplifies many problems involving vector spaces and linear transformations.

3. How do you find an orthonormal basis?

To find an orthonormal basis, you can use the Gram-Schmidt process. This involves starting with a set of linearly independent vectors and using orthogonalization and normalization techniques to transform them into an orthonormal set.

4. Can an orthonormal basis be used for any vector space?

No, an orthonormal basis can only be used for vector spaces that have an inner product defined. This includes Euclidean spaces and other abstract vector spaces that have a defined dot product or inner product.

5. How does an orthonormal basis relate to the concept of linear independence?

An orthonormal basis is a set of linearly independent vectors. This means that none of the vectors in the set can be written as a linear combination of the others. In other words, each vector in the set is necessary to span the entire vector space.

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