Graduate Drawing Graphs with f(x): A Beginner's Guide

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SUMMARY

This discussion focuses on the challenges of defining a mathematical function to replicate a graph derived from a 12 Hole Ocarina playing the note "e". Participants emphasize that while piecewise functions can approximate the graph, a Fourier decomposition provides a more accurate representation by capturing harmonic frequencies and their variations. The conversation highlights the importance of using spline routines for visual manipulation and suggests that both direct approximation and spectral analysis can yield valuable insights into the original signal.

PREREQUISITES
  • Understanding of Fourier decomposition and its applications in signal processing.
  • Familiarity with piecewise functions and their construction.
  • Knowledge of spline interpolation techniques for graphing.
  • Basic concepts of harmonic frequencies and their significance in sound analysis.
NEXT STEPS
  • Learn about Fourier Transform and its application in audio signal analysis.
  • Explore spline interpolation methods for creating smooth curves from discrete data points.
  • Research piecewise function construction and its use in approximating complex graphs.
  • Investigate the role of harmonic analysis in understanding musical notes and their frequencies.
USEFUL FOR

This discussion is beneficial for musicians, audio engineers, data analysts, and anyone interested in the mathematical representation of sound waves and graphing techniques.

btb4198
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function.png
How do I make a function that can draw this same graph ? Also, if i want to increase the frequency of the function, how do i do that ?
so I am thinking f(x) = sin(x) for -1<= f(x) =0.5; f(x) = e^(x)/10 for f(x)= <=1 ; f(x) = cos(x) for f(x) >=0.5
f(x) = -cos(x)
um... i do not think this is right.
help
 
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Is this the graph of something you measured? Or is it the graph of something you simulated?

In either case, given a graph on a certain interval (say, a time interval) it is in general not possible to define a function in terms of elementary functions (such as polynomials, harmonics, exponentials, etc.) that replicates said graph, even when you allow for piecewise definition.

In a sense, the graph itself is the definition of the function you are looking for.
 
hi, so that is graph of an 12 Hole Ocarina playing the note e.
wait I can't make a function out of it ?
 
btb4198 said:
hi, so that is graph of an 12 Hole Ocarina playing the note e.
wait I can't make a function out of it ?
Nice. From your graph you can see that there is a harmonic in the background (probably its frequency corresponds to your "e"), but there is something else on top of it that reflects the fact that you are close to producing an "e", but you do not manage to do that with mathematical perfection.

Probably a spectral decomposition would show a peak at the "e" frequency, but in addition there will be some much smaller mini-peaks around it.
 
If you just want to draw the graph and manipulate it in a visual sense then use ordinate samples and a spline routine . Some spread sheets can do this but it is not difficult to write a program .
 
A method commonly used in engineering computation is to break down the curve of interest into a sequence of segments where each segment can be defined with a simple function .
 
Nidum said:
A method commonly used in engineering computation is to break down the curve of interest into a sequence of segments where each segment can be defined with a simple function .
I think that is what the OP was trying to do.

Because it appears this is the recording of a real musical instrument playing an "e", to me it would provide most insight to Fourier decompose the recording, keep as many modes as one likes and use these to reconstruct an approximation to the original signal.

The OP could do both: direct approximation using piecewise definition (using e.g. splines, as Nidum suggested) and a spectral approximation, and compare.
 
Krylov said:
I think that is what the OP was trying to do.

Because it appears this is the recording of a real musical instrument playing an "e", to me it would provide most insight to Fourier decompose the recording, keep as many modes as one likes and use these to reconstruct an approximation to the original signal.

The OP could do both: direct approximation using piecewise definition (using e.g. splines, as Nidum suggested) and a spectral approximation, and compare.
Function2.png
 
I was trying to do the
Krylov said:
Nice. From your graph you can see that there is a harmonic in the background (probably its frequency corresponds to your "e"), but there is something else on top of it that reflects the fact that you are close to producing an "e", but you do not manage to do that with mathematical perfection.

Probably a spectral decomposition would show a peak at the "e" frequency, but in addition there will be some much smaller mini-peaks around it.
sorry,
I am not understanding what you are saying here...
 

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