Fourier analysis (Using Audacity)

In summary, the conversation discussed a project involving deconstructing musical instruments into their sinusoidal waves using Fourier analysis and the use of Audacity's plot spectrum tool. The issue of correlating the amplitude given by Audacity with the amplitude used as an input was brought up, and it was suggested to use a spectrum analyzer to compare the amplitudes at each frequency. Factors such as noise and equipment limitations were also mentioned as possible reasons for discrepancies in the amplitudes.
  • #1
Gameasy
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Homework Statement


I'm doing a project for my school, deconstructing musical instruments into their various sinusoidal waves. I understand the outlying theory behind Fourier analysis and found what seems like a simple way to do it in the newest version of Audacity.
Go to "Analyze", then "Plot spectrum". In the window it opens, you need to change the number given to the biggest number available.
This gives a close approximation of the frequencies the the function is made of (1 or 2 Hz off).
The issue is that I can't find a way to correlate the amplitude given for the frequencies with the amplitude I used as an input to make the original function. This happens no matter how I get the answer. Any idea what's happening?

Homework Equations




The Attempt at a Solution



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  • #2
for my attempt at a solution.

Hello,

Thank you for sharing your project with us. It sounds like you have a good understanding of Fourier analysis and are using a helpful tool in Audacity.

To address your issue with correlating the amplitude given for the frequencies with the amplitude used as an input, it may be helpful to understand how Audacity is calculating the amplitude for each frequency. Audacity uses the Fast Fourier Transform (FFT) algorithm to calculate the spectrum of a signal. This algorithm converts a time-domain signal into its frequency-domain representation, and the amplitude for each frequency is calculated based on the magnitude of the corresponding frequency component in the signal.

So in order to correlate the amplitude given by Audacity with the amplitude used as an input, you will need to have a way to measure the amplitude of the original signal at each frequency. This can be done using a spectrum analyzer or other similar tools. Once you have the amplitude at each frequency, you can compare it with the amplitude given by Audacity and see if there are any discrepancies.

It is also important to note that there may be some differences in the amplitudes due to factors such as noise in the signal or limitations in the recording equipment. However, if there are significant differences, it may be worth looking into the settings and parameters used in Audacity to make sure they are accurately representing the original signal.

I hope this helps and wish you the best of luck with your project! Keep up the great work in exploring the world of sound and music through Fourier analysis.
 

Related to Fourier analysis (Using Audacity)

1. What is Fourier analysis?

Fourier analysis is a mathematical technique used to decompose a complex signal into its individual frequency components. It can be used to analyze and understand the frequency content of a signal.

2. How is Fourier analysis used in Audacity?

Audacity is a digital audio workstation that allows users to perform Fourier analysis on an audio signal. This can be done by selecting the "Spectrum" view, which displays the frequency spectrum of the audio signal. Audacity also has built-in tools for applying Fourier transforms and filters to the audio signal.

3. What is the difference between Fourier analysis and Fourier transform?

Fourier analysis is the process of breaking down a signal into its individual frequency components, while Fourier transform is a mathematical operation that allows us to convert a signal from the time domain to the frequency domain. In other words, Fourier analysis is the concept, while Fourier transform is the tool used to perform the analysis.

4. What are the applications of Fourier analysis?

Fourier analysis has many applications in various fields, including signal processing, image processing, and data analysis. It is used to understand the frequency content of signals and to filter out unwanted noise or distortions. In addition, it is also used in compression techniques, such as MP3 audio compression.

5. Can Fourier analysis be performed on non-periodic signals?

Yes, Fourier analysis can be performed on both periodic and non-periodic signals. However, the results may differ for non-periodic signals as they do not have a repeating pattern. In this case, the Fourier transform is used to analyze the signal in the frequency domain.

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