Calculate, by hand, the DFT of cos(2*pi(fx*m + fy*n))

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In summary: The first term is just the geometric sum of a series, and the second term is just a constant added on top.
  • #1
Number2Pencil
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1

Homework Statement



Calculate, by hand, the DFT of cos(2*pi(fx*m + fy*n)). It should simplify to something simple. It should NOT be left as a summation.

Homework Equations



2D DFT Formula:
[tex]
\tilde{s(k,l)} = \sum_{m=0}^{M-1} \sum_{n=0}^{N-1} s(m,n) e^{-j 2 \pi (\frac{1}{M}mk + \frac{1}{N}ln)}
[/tex]

The Attempt at a Solution




[tex]
\tilde{s(k,l)} = \sum_{m=0}^{M-1} \sum_{n=0}^{N-1} cos(2 \pi (f_x m + f_y n)) e^{-j 2 \pi (\frac{1}{M}mk + \frac{1}{N}ln)}
[/tex]


One of Euler's Formulas:

[tex]
cos(u+v) = \frac{1}{2}(e^{ju + jv} + e^{-ju -jv})
[/tex]


After much algebra crunching, I wound up with this:

[tex]
\tilde{s(k,l)} = \sum_{m=0}^{M-1} \sum_{n=0}^{N-1} \left[ \frac{1}{2}e^{-j2 \pi
\frac
{-f_x m M N + m k N + l n M - f_y n M N}
{MN}
} + \frac{1}{2} e^{-j2 \pi
\frac
{f_x m M N + f_y n M N + m k N + l n M}
{MN}} \right]
[/tex]

I am really not sure how to simplify this double geometric sum. Does it look recognizable? Was there an earlier simplification I could take?
 
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  • #2
Consider just one of the two added terms. As a function of n, it's of the form exp(An+B) = exp(A)nexp(B). So isn't it just the sum of a geometric series?
 
  • #3
So if e^{An+B} = e^{An} e^{B}, then e^{B} simply acts as a constant for the internal geometric sum?

[(1-A^M)/(1-A)] e^{B} ?

And then I can take the geometric sum again?

The original cosine function is not separable...is it?
 
  • #4
Number2Pencil said:
So if e^{An+B} = e^{An} e^{B}, then e^{B} simply acts as a constant for the internal geometric sum?

[(1-A^M)/(1-A)] e^{B} ?

And then I can take the geometric sum again?
Looks ok to me.
 

Related to Calculate, by hand, the DFT of cos(2*pi(fx*m + fy*n))

1. What is the purpose of calculating the DFT of cos(2*pi(fx*m + fy*n)) by hand?

The purpose of calculating the DFT (Discrete Fourier Transform) of cos(2*pi(fx*m + fy*n)) by hand is to analyze the frequency components of the given signal. This can provide insights into the signal's behavior, such as its periodicity and dominant frequencies.

2. What is the formula for calculating the DFT of cos(2*pi(fx*m + fy*n))?

The formula for calculating the DFT of cos(2*pi(fx*m + fy*n)) is:
X[k] = (1/N) * Σn=0 to N-1 {cos(2*pi(fx*m + fy*n)) * e^(-2*pi*i*k*n/N)}
Where N is the number of samples, k is the frequency index, and i is the imaginary unit.

3. How do you interpret the results of the DFT calculation for cos(2*pi(fx*m + fy*n))?

The results of the DFT calculation for cos(2*pi(fx*m + fy*n)) represent the amplitude and phase of each frequency component present in the signal. The magnitude of the result at a certain frequency index indicates the strength of that frequency in the signal, while the angle represents the phase shift of the signal at that frequency.

4. Can the DFT of cos(2*pi(fx*m + fy*n)) be calculated using a computer?

Yes, the DFT of cos(2*pi(fx*m + fy*n)) can be easily calculated using computer software or programming languages. This is a more efficient and accurate method compared to calculating it by hand, especially for large datasets.

5. How does the sampling rate affect the DFT of cos(2*pi(fx*m + fy*n))?

The sampling rate, which is the number of measurements taken per unit time, affects the DFT of cos(2*pi(fx*m + fy*n)) in two ways. First, a higher sampling rate will result in a finer frequency resolution of the DFT. Second, the Nyquist-Shannon sampling theorem states that the sampling rate must be at least twice the highest frequency component in the signal for accurate reconstruction. Therefore, a lower sampling rate may lead to aliasing in the DFT results.

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