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

Jamin2112
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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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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?
 
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?
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
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