How can I find the Fourier coefficients for a shifted sawtooth wave?

AI Thread Summary
To find the Fourier coefficients for a shifted sawtooth wave, it is essential to recognize that Fourier series apply only to periodic signals. The first step involves converting the sawtooth graph into a mathematical formula over one period, typically from -π to π. The signal can be analyzed by breaking it into manageable parts for integration. If the signal is not periodic, a Fourier Transform may be more appropriate. Understanding these properties is crucial for accurately determining the coefficients.
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Homework Statement


Recently in my signals class,we got to the chapter of Fourier series.We have learned that there are some basic graphs that can be described with Fourier series (sawtooth,square pulse etc) and so far i have understood their respective Fourier formulas.The problem i face though,is that when i have an exercise where i need to find the Fourier of a similar signal (i.e a shifted sawtooth wave),don't know how to do it.Here is a specific example:we have the Fourier series for the sawtooth wave:x(t)=1/2-[00]\sum[n=1] (4/(2n-1)^2*pi ^2) cos {(2n-1)2pi/T *t} and the question is what are the Fourier coefficients for the sawtooth wave which starts from -0.1 and the max. point (amplitude) is 0.4.Below i have attached the graph of that signal.

P.S:Sorry for my poor English.I am really looking forward to the answer.

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The Attempt at a Solution


The professor told us that it can be solved using the Fourier properties.
 

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First, I will assume your signal goes on forever in the same manner forever. This is a requirement for using the Fourier series. It only works on periodic signals. If what you show is all there is, you want to use a Fourier Transform. It works for aperiodic signals.

Given a periodic signal, the first thing you want to to is convert the saw tooth graph into a formula for x between -pi to pi (the period of the signal). See http://en.wikipedia.org/wiki/Fourier_series about half way down for a simple example. Your signal is a bit more complicated but it can be converted by breaking it into parts that can be integrated separately and then added together.
 
You can use Fourier series for signals of finite duration as long as you don't care what happens before or afterwards.
 
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