How to Apply Fourier Analysis with Octave for Signal Transfer Functions?

In summary, the conversation was about finding the outgoing signal in relation to time using a known transfer function and a periodic piecewise function for the incoming signal. The transfer function used was S(\omega)=\sqrt{10}(\frac{i\omega/\omega_2}{1+i\omega/\omega_2})^2, where \omega_2=9301.85 rad/s. The speaker also mentioned having a solution for the outgoing signal but was unsure if it was done correctly. They shared their source code which involved sampling the incoming signal, taking the fast Fourier transform, and using a filter function. They asked for feedback on their approach.
  • #1
MisterSpline
1
0
Hey everyone,
So what I'm trying to do is to find the outgoing signal in function of the time, when
the transfer function of the filter is known and the incoming signal is a periodic piecewise function.
The incoming signal I(t)= 0 for -T/2<t<-T/4
[tex]=\cos(\frac{t\pi}{T}) [/tex] for -T/4<=t<T/4
= 0 fot T/4<=t<T
And the transfer function I'm using is
[tex] S(\omega)=\sqrt{10}(\frac{i\omega/\omega_2}{1+i\omega/\omega_2})^2, [/tex]
where [tex]\omega_2=9301.85 rad/s [/tex].

I have a solution for the outgoing signal U(t) but I'm not sure I'm doing it right.
This is my source code:

T=1*10^(-3);w2=9301.82; t=-0.005:1/100000:0.005;
y=incoming(t,T); %Sampling my incoming signal
Y=fft(y); %taking the fast Fourier transform
N=length(Y);
freq=[0:N-1];
U=Y.*filter(freq,w2) %where filter is the transfer function
u=ifft(U);
plot(t,ifftshift(u));
 
Last edited:
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  • #2
%plotting my outgoing signalCan someone help me out and tell me if this is the right way to do it?Thanks in advance!
 

1. What is Fourier analysis?

Fourier analysis is a mathematical technique used to break down complex signals or data into simpler components. It is based on the principle that any signal can be represented as a combination of sinusoidal functions.

2. How is Octave used in Fourier analysis?

Octave is an open-source software program that is commonly used for performing Fourier analysis. It provides functions and algorithms for calculating Fourier transforms and manipulating the resulting data.

3. What is the purpose of using Fourier analysis in scientific research?

Fourier analysis is a powerful tool for understanding and analyzing complex data in fields such as physics, engineering, and biology. It can reveal hidden patterns and relationships in data that are not easily apparent from the original form.

4. What are some practical applications of Fourier analysis?

Fourier analysis has many practical applications in various fields, including signal processing, image and sound compression, data filtering and smoothing, and pattern recognition. It is also used in fields such as astronomy, geophysics, and medical imaging.

5. Are there any limitations to using Fourier analysis with Octave?

While Octave is a powerful tool for performing Fourier analysis, it does have some limitations. For example, it may not be suitable for analyzing data with irregular or non-uniformly spaced samples. Additionally, the accuracy of the results may be affected by the quality of the input data and the chosen parameters for the analysis.

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