Hey Everybody,
I am currently working on a basic signals and systems filtering project(attached) and I wanted to ask you guys some general questions as I go along through the project to make sure I'm learning this stuff correctly.
My first question is about estimating the natural or fundamental frequency of a signal graphically.
The wave is that of a bugle. After some research I read that an instrument has a few fundamental frequencies and those frequencies are easily excited. I assume that the high magnitude frequencies on my frequency vs. magnitude graph are multiples of my wave's fundamental frequency.
Is this assumption correct?
With that assumption I used the graphical zoom function to zoom in on all of the peaks and I noticed that they were almost evenly distributed. I assumed that the difference in these peaks was the fundamental frequency.
Is this an accurate way of doing this?
Also, After this step we were required to design an ideal filter to filter out extraneous portions of the wave. This means low frequencies that would sound like hums and possibly high frequencies like cracking right?
Thanks,
I am currently working on a basic signals and systems filtering project(attached) and I wanted to ask you guys some general questions as I go along through the project to make sure I'm learning this stuff correctly.
My first question is about estimating the natural or fundamental frequency of a signal graphically.
The wave is that of a bugle. After some research I read that an instrument has a few fundamental frequencies and those frequencies are easily excited. I assume that the high magnitude frequencies on my frequency vs. magnitude graph are multiples of my wave's fundamental frequency.
Is this assumption correct?
With that assumption I used the graphical zoom function to zoom in on all of the peaks and I noticed that they were almost evenly distributed. I assumed that the difference in these peaks was the fundamental frequency.
Is this an accurate way of doing this?
Also, After this step we were required to design an ideal filter to filter out extraneous portions of the wave. This means low frequencies that would sound like hums and possibly high frequencies like cracking right?
Thanks,
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