Periodic Function Fourier Series: Proving with Trigonometric Equations

Can you explain your approach in more detail?In summary, the conversation discusses a periodic function of period 2π defined by f(t) = t/2, with 0 < t < 2π. The goal is to show that the trigonometric Fourier series of f(t) is given by f(t) = π/2 - ∑(1/n)sin(nt). The conversation also touches on finding the constant C, with a suggested value of π/4 instead of π/2. Various equations and attempts at a solution are mentioned, including using the fact that the function is odd and computing A_n and b_n in the Fourier series.
  • #1
icystrike
445
1

Homework Statement



A periodic function of period [tex]2\pi[/tex] is defined by:
[tex] f(t)=\frac{t}{2} , 0<t<2\pi [/tex]

Show that the trigonometric Fourier series of f(t) is given by:
[tex]f(t)=\frac{\pi}{2} - \sum_{n=1}^{\infty} \frac{1}{n}sin(nt)[/tex]

Homework Equations


The Attempt at a Solution



I've gotten [tex]\frac{\pi}{4}[/tex] for constant C instead of [tex]\frac{\pi}{2}[/tex]
 
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  • #2
What have you done so far, show us your working.
 
  • #3
Since function is odd, An = 0.

Bn = [tex]- \frac{1}{2\pi} \frac{2\pi}{n} = -\frac{1}{n} [/tex]

Thats for now...
 
  • #4
My advice is to write:

[tex]
f(t)=a_{0}+\sum_{n=-\infty}^{\infty}a_{n}\sin nt+b_{n}\cos nt
[/tex]
 
  • #5
[tex]

f(t)=\sum_{n=-\infty}^{\infty} \frac{(1)^{n+1}}{n}\sin nt

[/tex]
 
  • #6
So you compute te A_n's and b_n is the usual way, what you have done with this?
 
  • #7
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attachment.php?attachmentid=33465&stc=1&d=1300961751.jpg
 

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  • #8
Hmm, I am at a loss.
 

1. What is a simple Fourier transform?

A simple Fourier transform is a mathematical technique used to decompose a signal into its frequency components. It takes a time-domain signal and converts it into a frequency-domain representation.

2. How does a simple Fourier transform work?

A simple Fourier transform works by breaking down a signal into its individual sinusoidal components, each with a specific frequency and amplitude. It then combines these components to recreate the original signal.

3. What are the applications of a simple Fourier transform?

A simple Fourier transform is commonly used in signal processing, data analysis, and image processing. It is also used in fields such as physics, chemistry, and engineering to analyze and interpret complex data.

4. What is the difference between a discrete Fourier transform and a simple Fourier transform?

A discrete Fourier transform is used for discrete signals, while a simple Fourier transform is used for continuous signals. This means that a discrete Fourier transform is used for signals that are only defined at specific points, while a simple Fourier transform is used for signals that are defined over a continuous range.

5. Are there any limitations to using a simple Fourier transform?

While a simple Fourier transform is a powerful tool, it does have its limitations. It works best for signals that are periodic and have a finite number of frequency components. It also assumes that the signal is stationary, meaning it does not change over time.

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