Can anyone explain this regarding to fourier series and bessel series expansion?

In summary: So you mean the denominator is the full range( say 2\pi) even the f(x) only non zero from o<x<\pi This will cover it according to the formula of fourier/bessel series...
  • #1
yungman
5,718
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For finding series expansion solution of problems like

f(x) = h(x) for 0<x<1
f(x) = 0 for 1<x<2

0<x<2

Where the Fourier series expansion only integrate from x=0 to x=1 only and totally ignor the portion of x=1 to x=2.

This is also true for Fourier bessel series expansion also.

I never see the prove, this only show up in the work problems. Can anyone show me the prove of this.
 
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  • #2
Your nth coefficient in your expansion is something like
[tex]
a_n = \int_0^2 f(x) q_n(x) dx
[/tex]
where [tex]q_n[/tex] is a sin, cos, bessel, etc.

If f is zero over [1,2], how can you simplify this integral?

jason
 
  • #3
jasonRF said:
Your nth coefficient in your expansion is something like
[tex]
a_n = \int_0^2 f(x) q_n(x) dx
[/tex]
where [tex]q_n[/tex] is a sin, cos, bessel, etc.

If f is zero over [1,2], how can you simplify this integral?

jason

Thanks for the reply, I know exactly how to solve the problem and I know the answer is 0 when integrate from x=1 to x=2.

I just can not "see" it in English!
 
  • #4
yungman said:
Thanks for the reply, I know exactly how to solve the problem and I know the answer is 0 when integrate from x=1 to x=2.

I just can not "see" it in English!

I am probably missing something, but to me it looks like you just wrote it in English. So I'm not sure what more you are hoping to "see".

jason
 
  • #5
I think I see what is bothering you. In general in eigenfunction expansions, whatever their form, you have a set of eigenfunctions φn satisfying an orthogonality property with respect to some weight function w on an interval (a,b), and you want to express some function f in an eigenfunction expansion.

[tex] f(x) = \sum_{k=1}^\infty c_k\phi_k(x)[/tex]

You multiply by φn and integrate termwise with respect to the weight function:

[tex]\int_a^b f(x)\phi_n(x)w(x)dx=\sum_{k=1}^\infty\int_a^b c_k\phi_k(x)\phi_n(x)w(x)dx=
c_n\int_a^b \phi_n^2(x)w(x)dx[/tex]

using the orthogonality of the φn's. This gives you the formula for cn:

[tex]c_n=\frac{\int_a^b f(x)\phi_n(x)w(x)dx}{\int_a^b \phi_n^2(x)w(x)dx}[/tex]

The denominator is frequently constant as, for example, in the classical sine-cosine series it is [itex]2\pi[/itex], and we tend to forget where it came from.

Now to get to what I think is bothering you. You are thinking that if f(x) is zero on part of the (a,b) interval so you only integrate over part of the interval, so what the φn's are on the rest of the interval don't matter. But notice, in the full formula for the cn, you still go from a to b in the denominator. Again, that may be a constant so you don't notice it. It's like in the ordinary sine cosine series, you don't change the [itex]1/2\pi[/itex] out front when you integrate over just part of the interval because f(x) is partly zero.
 
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  • #6
LCKurtz said:
I think I see what is bothering you. In general in eigenfunction expansions, whatever their form, you have a set of eigenfunctions φn satisfying an orthogonality property with respect to some weight function w on an interval (a,b), and you want to express some function f in an eigenfunction expansion.

[tex] f(x) = \sum_{k=1}^\infty c_k\phi_k(x)[/tex]

You multiply by φn and integrate termwise with respect to the weight function:

[tex]\int_a^b f(x)\phi_n(x)w(x)dx=\sum_{k=1}^\infty\int_a^b c_k\phi_k(x)\phi_n(x)w(x)dx=
c_n\int_a^b \phi_n^2(x)w(x)dx[/tex]

using the orthogonality of the φn's. This gives you the formula for cn:

[tex]c_n=\frac{\int_a^b f(x)\phi_n(x)w(x)dx}{\int_a^b \phi_n^2(x)w(x)dx}[/tex]

The denominator is frequently constant as, for example, in the classical sine-cosine series it is [itex]2\pi[/itex], and we tend to forget where it came from.

Now to get to what I think is bothering you. You are thinking that if f(x) is zero on part of the (a,b) interval so you only integrate over part of the interval, so what the φn's are on the rest of the interval don't matter. But notice, in the full formula for the cn, you still go from a to b in the denominator. Again, that may be a constant so you don't notice it. It's like in the ordinary sine cosine series, you don't change the [itex]1/2\pi[/itex] out front when you integrate over just part of the interval because f(x) is partly zero.

Thanks for the reply. I have been busy on another problem, have not been able to get to this until now.

So you mean the denominator is the full range( say [itex]2\pi[/itex]) even the f(x) only non zero from o<x<[itex]\pi[/itex] This will cover it according to the formula of fourier/bessel series expansion.

Thanks
 

1. What is a Fourier series?

A Fourier series is a mathematical representation of a periodic function as a sum of sine and cosine functions. It is used to analyze and approximate various types of functions, including non-periodic ones.

2. How is a Fourier series calculated?

A Fourier series is calculated using a mathematical formula that involves integrating the function over a specific interval and multiplying it by sine and cosine functions with different frequencies and amplitudes.

3. What are Bessel series?

Bessel series are another type of mathematical series that are used to represent functions, particularly those that involve circular or cylindrical symmetry. They are similar to Fourier series, but they use Bessel functions instead of sine and cosine functions.

4. How is a Bessel series expansion different from a Fourier series expansion?

While both series expansions can be used to represent functions, they are different in terms of the types of functions they are best suited for. Bessel series are more appropriate for functions with circular or cylindrical symmetry, while Fourier series are better for analyzing periodic functions.

5. Why are Fourier and Bessel series important in science and engineering?

Fourier and Bessel series are important in science and engineering because they provide a way to represent and analyze complex functions in a simpler form. They are used in a wide range of applications, including signal processing, image and sound compression, and solving differential equations.

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