I'm confused by what the professor means on this Fourier Series proble

In summary, the conversation discusses the use of fft(x) to calculate Fourier coefficients for a function fitted through sample points, and the confusion around the values of 1/31 and c in the context of the problem. The conversation also mentions using the MATLAB function odeset to change absolute and relative tolerance for a different problem.
  • #1
Jamin2112
986
12

Homework Statement



See the second bullet point on this page: http://facweb.northseattle.edu/rjenne/e240w13flr/hwflr/feb21/e240w13hwfeb21.pdf

Homework Equations



So I know that fft(x) for a bunch of sample points x={x1, x2, ..., xn} returns the n Fourier coefficients for a function fitted through those sample points.

The Attempt at a Solution



So I'm a little confused about what the 1/31 and the c mean in the context of this problem. What I'm trying to do, ultimately, is use the Fast Fourier Transform algorithm on 31 equally spaced sample points on the domain [1, 4] to reconstruct the function on 3001 equally spaced sample points on the same domain.

Thoughts?
 
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  • #2
Jamin2112 said:
So I know that fft(x) for a bunch of sample points x={x1, x2, ..., xn} returns the n Fourier coefficients for a function fitted through those sample points.

[...]

So I'm a little confused about what the 1/31 and the c mean in the context of this problem.

How is the Fourier transform normalized? And can you see any link between what I put in bold there?
 
  • #3
DrClaude said:
How is the Fourier transform normalized? And can you see any link between what I put in bold there?

Now I've figured out that problem, but I'm confused on a different problem where I have to use the MATLAB function odeset to change absolute and relative tolerance. Do you know how to do that?
 

1. What is a Fourier Series?

A Fourier Series is a mathematical representation of a periodic function as a sum of sinusoidal functions. It is used to analyze and approximate a wide variety of functions and is commonly used in signal processing and differential equations.

2. Why do we use Fourier Series?

Fourier Series allow us to break down complex functions into simpler components, making it easier to analyze and understand them. They also have numerous practical applications, such as in image and sound processing, and in solving differential equations.

3. How do I calculate a Fourier Series?

To calculate a Fourier Series, you will need to know the period of the function and its values over one period. Then, you can use the Fourier Series formula or tables to find the coefficients of the sinusoidal functions that make up the series.

4. What does it mean when the professor says "convergence" in relation to the Fourier Series?

Convergence refers to the behavior of the Fourier Series as the number of terms increases. If a series converges, it means that the sum of the terms approaches a finite value. In the context of Fourier Series, it is important to understand the convergence of the series in order to accurately approximate a function.

5. Can you give an example of a Fourier Series problem?

Sure, an example of a Fourier Series problem could be finding the Fourier Series representation of the function f(x) = x on the interval [-π, π]. This would involve finding the coefficients of the sine and cosine terms in the series and determining the convergence of the series for this function.

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