Using Fourier analysis to find frequency-amplitude spectrum?

In summary, to create a magnitude spectrum for a square wave with an arbitrary number of co-efficients, a programmer would need to know the steps to find a Fourier transformation and the formulas for the Fourier coefficitents.
  • #1
jamdr
13
0
The signal is from a voltage supply. I see lots of pages on the internet about this, such as this one, which shows what the magnitude spectrum looks like for a square wave with an arbitrary number of co-efficients. But how would I actually create that graph myself?
 
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  • #2
jamdr said:
The signal is from a voltage supply. I see lots of pages on the internet about this, such as this one, which shows what the magnitude spectrum looks like for a square wave with an arbitrary number of co-efficients. But how would I actually create that graph myself?

Is this a question of COMPUTER PROGRAMMING,MATHS or PHYSICS??

Think deep...To me it looks like pogramming...What programming languages do u know?

Daniel.
 
  • #3
It's a math question I suppose. I need to know the steps to find a Fourier transformation. I know that MATLAB and other computer programs can solve this type of problem, but I want to understand the math behind it.
 
  • #4
the Fourier coefficitents are calculated using the formulas

[tex] F(x) = \sum^{\infty} _{0} A_{n}\cos\left(\frac{n\pi x}{a} \right ) + B_{n}\sin\left (\frac{n\pi x}{a}\right )[/tex]

where

[tex] A_{n} =\frac{1}{a} \int _{-a} ^{a} F(x)\cos\left (\frac{n\pi x}{a}\right ) dx [/tex]

and

[tex] B_{n} =\frac{1}{a} \int _{-a} ^{a} F(x)\sin\left (\frac{n\pi x}{a} \right ) dx [/tex]

from here plug in the periodic function and do the integrals...
 
  • #5
Dr Transport said:
the Fourier coefficitents are calculated using the formulas

[tex] F(x) = \sum^{\infty} _{0} A_{n}\cos\left(\frac{n\pi x}{a} \right ) + B_{n}\sin\left (\frac{n\pi x}{a}\right )[/tex]

where

[tex] A_{n} =\frac{1}{a} \int _{-a} ^{a} F(x)\cos\left (\frac{n\pi x}{a}\right ) dx [/tex]

and

[tex] B_{n} =\frac{1}{a} \int _{-a} ^{a} F(x)\sin\left (\frac{n\pi x}{a} \right ) dx [/tex]

from here plug in the periodic function and do the integrals...

Wait, what is a?
 
  • #7
Thanks for the help Dr. Transport. But in the end I ended up using this formula:

[tex]f_n=\frac{1}{T}\int_0^T v(t) e^{-j n \omega t} dt[/tex]

where n is some arbitrary number of coefficients. Also, n is the index of f (an array). Then I plotted [tex]\overrightarrow{\left|f\right|}_n[/tex] versus [tex]\frac{n}{T}[/tex]

I don't fully understand this, but it seemed to work.
 
Last edited:
  • #8
the last equation stated is complex Fourier series while the earlier stated equation is trigonometry Fourier series. I'm done.
 

FAQ: Using Fourier analysis to find frequency-amplitude spectrum?

What is Fourier analysis and how does it work?

Fourier analysis is a mathematical technique used to decompose a complex signal into its individual frequency components. It works by representing a signal as a combination of sine and cosine waves of varying frequencies and amplitudes.

How is Fourier analysis used to find the frequency-amplitude spectrum?

By applying Fourier analysis to a signal, the resulting frequency-amplitude spectrum shows the different frequency components present in the signal and their corresponding amplitudes. This can help identify any dominant frequencies or patterns in the signal.

What type of signals can be analyzed using Fourier analysis?

Fourier analysis can be applied to any signal that is periodic or can be represented as a sum of periodic functions. This includes signals in the time domain, such as audio and vibration signals, as well as signals in other domains, such as images and video.

Are there any limitations to using Fourier analysis?

While Fourier analysis is a powerful tool for analyzing signals, it does have some limitations. One limitation is that it assumes the signal is periodic, which may not always be the case in real-world applications. Additionally, the accuracy of the results can be affected by factors such as sampling rate and noise in the signal.

How is the frequency resolution determined in Fourier analysis?

The frequency resolution in Fourier analysis is determined by the length of the signal being analyzed. A longer signal will have a higher frequency resolution, meaning smaller changes in frequency can be detected. However, this also means that a longer signal will take more time to analyze. The frequency resolution can also be improved by using a higher sampling rate.

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