Fourier series - by Ray Betz: Difference between revisions

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If <math>k=n</math> then,
If <math>k=n</math> then,


<math> \sum_{k=-\infty}^\infty \alpha_k \int_{-\frac{T}{2}}^\frac{T}{2} e^ \frac {j 2 \pi (k-n) t}{T} dt = \int_{-\frac{T}{2}}^\frac{T}{2} 1 dt = T</math>
<math> \int_{-\frac{T}{2}}^\frac{T}{2} e^ \frac {j 2 \pi (k-n) t}{T} dt = \int_{-\frac{T}{2}}^\frac{T}{2} 1 dt = T</math>


If <math>k \ne n </math> then,
If <math>k \ne n </math> then,


<math> \sum_{k=-\infty}^\infty \alpha_k \int_{-\frac{T}{2}}^\frac{T}{2} e^ \frac {j 2 \pi (k-n) t}{T} dt = 0 </math>
<math> \int_{-\frac{T}{2}}^\frac{T}{2} e^ \frac {j 2 \pi (k-n) t}{T} dt = 0 </math>


We can simplify the above two conclusion into one equation.
We can simplify the above two conclusion into one equation.

Revision as of 17:15, 23 October 2005

Fourier Series

If

  1. Dirichlet conditions are satisfied

then we can write

The above equation is called the complex fourier series. Given , we may determine by taking the inner product of with . Let us assume a solution for of the form . Now we take the inner product of with .

If then,

If then,

We can simplify the above two conclusion into one equation.

So, we may conclude

Orthogonal Functions

The function and are orthogonal on if and only if .

The set of functions are orthonormal if and only if .

Linear Systems

I may come back to this latter...

Fourier Series (indepth)

I would like to take a closer look at in the Fourier Series. Hopefully this will provide a better understanding of .

We will seperate x(t) into three parts; where is negative, zero, and positive.

Now, by substituting into the summation where is negative and substituting into the summation where is positive we get:

Recall that

If is real, then . Let us assume that is real.

Recall that Here is further clarification on this property

So, we may write:

Fourier Transform

Fourier transforms emerge because we want to be able to make Fourier expressions of non-periodic functions. We can take the limit of those non-periodic functions to get a fourier expression for the function.

Remember that:


So,

From the above limit we define and .

We can take the derivitive of and then put in terms of the reverse fourier transform.