Orthonormal Basis Homework: Gram-Schmidt Process w/ Inner Product

In summary, the conversation discusses the application of the Gram-Schmidt procedure to convert a basis of {1,2x,3x^2} using the inner product <p,q> = \int p(x)q(x) from 0 to 1. The individual follows the procedure and attempts to convert the basis to an orthonormal basis, but encounters issues with the inner product. They discuss the condition for alpha and note that it cannot be a function of x.
  • #1
maggie56
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Homework Statement


Hi, i am applying the gram-schmidt procedure to a basis of {1,2x,3x^2} with inner product <p,q> = [tex]\int p(x)q(x) [/tex] from 0 to 1.

i am unsure what to do with the inner product

Homework Equations





The Attempt at a Solution



I have followed the procedure i have for converting this basis to an orthonormal basis, where v1=1, v2=2x, v3=3x^2 are the initial vectors

i let b1=v1=1

so b2 = v2 + [tex]\alpha[/tex] v1 = 2x + [tex]\alpha[/tex]
then <b1,b2> = 0 = <1, 2x + [tex]\alpha[/tex] >
which gives me [tex]\alpha[/tex] = -2x but then b2=0
I get a result of 0 for b3 also, and think i must have something wrong because i haven't used the inner product <p,q> = [tex]\int p(x)q(x) [/tex] from 0 to 1. but can't see what to do with this.


thanks
 
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  • #2
ok so you want the inner product to be zero, so the vectors orthogonal
[tex] <b1,b2> = 0 = <1, 2x + \alpha > =\int_0^1 dx 2x+\alpha = (x^2 + \alpha.x)|_0^1[/tex]

so this is the condition for alpha

notes alpha is a scalar multiplier of the basis vectors and cannot be a function of x.
 

1. What is an orthonormal basis?

An orthonormal basis is a set of vectors in a vector space that are both orthogonal (perpendicular) and normalized (unit length). This means that each vector in the set is perpendicular to all other vectors and has a magnitude of 1.

2. What is the Gram-Schmidt process?

The Gram-Schmidt process is a method for creating an orthonormal basis from a set of linearly independent vectors. It involves a series of orthogonal projections and normalization to transform the original vectors into an orthonormal set.

3. What is the significance of an orthonormal basis?

An orthonormal basis is significant because it simplifies many mathematical calculations and allows for easier visualization and manipulation of vectors. It is also a fundamental concept in linear algebra and is used in a variety of applications, such as signal processing and data compression.

4. How is the Gram-Schmidt process related to inner product?

The Gram-Schmidt process uses the inner product (also known as dot product) to determine the orthogonal projections in each step. The inner product is a mathematical operation that takes two vectors and returns a scalar value. It is used to measure the angle between two vectors and to calculate the length of a vector.

5. Why is the Gram-Schmidt process important in linear algebra?

The Gram-Schmidt process is important in linear algebra because it allows for the creation of an orthonormal basis from a set of linearly independent vectors. This is crucial in many applications, as it simplifies calculations and allows for a better understanding and manipulation of vectors in a vector space.

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