Linear Algebra, Adjoint of a Linear Operator and Inner Product Spaces

In summary, the conversation discusses finding a vector y in an inner product space V and linear transformation g that satisfies the equation g(x) = <x,y> for all x in V. The particular case being discussed is V=P2(R) with the given inner product and linear transformation. The conversation also mentions a theorem from the textbook and the answer given in the back of the book, but the individual is unsure of how to arrive at that answer. They share their attempt at a solution using an orthonormal basis and the inner product, but note that they are unsure of why the inner product was given. The expert recommends using Gram-Schmidt to find an orthonormal basis and then proceeding with the same method.
  • #1
PrincessEmily
2
0

Homework Statement


For each of the following inner product spaces V (over F) and linear transformation g:=V [tex]\rightarrow[/tex] F, find a vector y such that g(x) = <x,y> for all x element of V.

The particular case I'm having trouble with is:

V=P2(R), with <f,h>=[tex]\int_0^{1}[/tex] f(t)h(t)dt , g(f)=f(0)+f'(1).

From the textbook Linear Algebra (fourth edition) by Friedburg and Friends.
p. 365 problem #2. c)

Homework Equations



From the theorem given in the book, I know that:
y=[tex]\sum_{i=1}^{n}[/tex][tex]\overline{g(v_i)}[/tex]vi

is a vector such that g(x)=<x,y> for all x element of V
where B={v1,v2...vn} is an orthonormal basis for V.

I also know that the answer (printed in the back of the book) is y=210x2 - 204x + 33 but I have no idea how to get this answer!

The Attempt at a Solution


I assigned B={1,x,x2}={e1,e2,e3} as an orthornormal basis for P2(R) (the space of polynomials of degree less than or equal to 2 over R).
Then I did:
y=g(1)e1 + g(x)e2 + g(x2)e3 because the field is R, I know that [tex]\overline{g(anything)}[/tex] = g(anything) so I don't worry about the conjugate of g(anything)
=(1+0)e1 + (0+1)e2 + (0+2)e3
=1e1 + 1e2 + 2e3
= 1 + x + 2x2

But this isn't the answer from the book... I also have no idea why the inner product was defined for me, I assumed to test my y vector?
I did I similar problem (part a) over R3 using the technique I applied above, and it worked fine.
Any help would be greatly appreciated.
Thanks :)
 
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  • #2
If, as you state, {e_1,e_2,e_3}= {1,x, x^2} are an orthonormal basis then it would follow that

[tex]\int_0^1 e_i e_j dx[/tex]

would be 0 or 1.

The inner product was given to you so that you would know what the inner product was, since there are infinitely many inner products. For example, if in your R^3 example I defined {x,y} as <x,y>/2, then you would find a different answer for the question 'find y such that g(x) = {x,y}' than 'find y such that g(x)=<x,y>'.
 
  • #3
Thank you :)
So I should Gram-Schmidt the basis I have (and then normalize them) to find an orthonormal basis, and then do what I was doing, right?
 

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with the study of linear equations, vector spaces, and linear transformations. It involves the use of matrices, vectors, and other mathematical tools to solve problems related to systems of linear equations.

2. What is the adjoint of a linear operator?

The adjoint of a linear operator is a fundamental concept in linear algebra that refers to the transpose of the matrix of the linear operator. It is also known as the conjugate transpose, and it represents a mapping from one vector space to its dual space.

3. How is the adjoint of a linear operator calculated?

The adjoint of a linear operator is calculated by first taking the transpose of the matrix representing the linear operator and then taking the complex conjugate of each element in the resulting matrix. This can be done by simply flipping the matrix over its main diagonal.

4. What are inner product spaces?

An inner product space is a vector space equipped with an inner product, which is a mathematical operation that takes in two vectors and produces a scalar value. It is a generalization of the dot product in Euclidean space and is used to define notions of length, angle, and orthogonality.

5. What are some applications of linear algebra and inner product spaces?

Linear algebra and inner product spaces are used in various fields, including physics, engineering, computer science, and statistics. They are used to solve problems related to linear systems, optimization, data analysis, and image processing. They also have applications in quantum mechanics, signal processing, and machine learning.

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