Fourier Analasys - Inner Product Spaces

In summary, The first assignment deals with showing that the function fn converges to 0 in L2[0,1] for n > 0. However, it does not converge to zero uniformly on [0,1]. The second assignment involves finding the L2[-\pi, \pi] orthogonal projection of the function f(x) = x2 onto a given space Vn. The orthonormality of the basis is tested, and then the orthogonal projection is found by taking the inner product of each basis with the function. The result is a sum of terms, with the number of terms increasing with n. The use of 1/2π instead of 1 is debatable.
  • #1
Ylle
79
0

Homework Statement


I have two assignments I have some problems with.

The first one:

For n > 0, let

fn(t) = {1, 0 [tex]\leq[/tex] t [tex]\leq[/tex] 1/n
0, otherwise

Show that fn [tex]\rightarrow[/tex] 0 in L2[0,1]. Show that fn does NOT converge to zero uniformly on [0,1]


The second one:
Find the L2[-[tex]\pi[/tex], [tex]\pi[/tex]] orthogonal projection of the function f(x) = x2 onto the space Vn [tex]\subset[/tex] L2[-[tex]\pi[/tex], [tex]\pi[/tex]] spanned by

{1, sin(jx)/sqrt([tex]\pi[/tex]), cos(jx)/sqrt([tex]\pi[/tex]); j =1,...,n}
for n = 1. Repeat this exercise for n= 2 and n = 3.



Homework Equations





The Attempt at a Solution


For the first one, I will take the integral:
|fn|2 = int(0 to 1/n) (1)^2 dt = 1/n - and therefor it converges to 0 for n -> infinite.

It's the second part of this I'm not sure about. I'm not sure how to explain it. Any help ?


For the second one, I first test if the basis' is orthonormal, but first taking the inner product of each of them <1, sin(jx)/sqrt([tex]\pi[/tex])>, <1, cos(jx)/sqrt([tex]\pi[/tex])> and <sin(jx)/sqrt([tex]\pi[/tex]), cos(jx)/sqrt([tex]\pi[/tex])> to find out they are all = 0.

And then I take the inner product of every basis <1,1>, <sin(jx)/sqrt([tex]\pi[/tex]), sin(jx)/sqrt([tex]\pi[/tex])> and so on, to find out that 1 is not 1, but 2*pi. So I normalize that one by dividing it with the 2*pi, and then I have an orthonormal basis, since the other to are have the length 1.

And then to find the orthogonal projection I say:
<x2, 1/(2*pi)>1/2*pi + <x2, sin(jx)/sqrt([tex]\pi[/tex])>sin(jx)/sqrt([tex]\pi[/tex]) + <x2, cos(jx)/sqrt([tex]\pi[/tex])>cos(jx)/sqrt([tex]\pi[/tex])

And since I do it for j, and not a 1, 2 or 3, I guess I really don't need to show it for 1, 2 or 3, since it's only some different integrals that make the difference +


Well, I hope you can help me a bit.


Regards
 
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  • #2
For problem 1, showing that the convergence is not uniform is very easy. I don't say that to make you feel bad, but rather as a hint. What is the definition of uniform convergence?

For problem 2, the answer in the n=1 case will be a sum of 3 terms, in the n=2 case a sum of 5 terms, and in the n=3 case a sum of 7 terms. I couldn't tell whether or not you realized that.

Perhaps someone else can comment about whether your use of 1/2π instead of 1 is correct, because I always use the convention 2π=1 (just kidding a little, but not completely). Maybe you should use 1/√(2π).
 

FAQ: Fourier Analasys - Inner Product Spaces

What is Fourier Analysis?

Fourier Analysis is a mathematical tool used to decompose a function into its constituent frequency components. It is based on the concept that any periodic function can be represented as a sum of simple sinusoidal functions with different frequencies and amplitudes.

What is an Inner Product Space?

An Inner Product Space is a vector space where an inner product is defined. The inner product is a mathematical operation that takes two vectors as inputs and produces a scalar as an output. It is used to measure the angle between two vectors and the length of a vector.

What is the relationship between Fourier Analysis and Inner Product Spaces?

Fourier Analysis can be applied to functions defined in an Inner Product Space. The inner product of two functions in the space can be used to calculate the Fourier coefficients, which represent the amplitude and phase of each frequency component in the function's Fourier series.

What are the applications of Fourier Analysis in real life?

Fourier Analysis has many applications in different fields, including signal processing, image and sound compression, and data analysis. It is also commonly used in physics, engineering, and mathematics to study periodic phenomena.

What are some limitations of Fourier Analysis?

Fourier Analysis is limited to analyzing periodic functions and cannot be applied to non-periodic functions. It also assumes that the function is continuous and has a finite number of discontinuities. In some cases, the complex calculations involved in Fourier Analysis can also be computationally expensive and time-consuming.

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