iii.Since this is real data and you have the recording times, find the times between each sample
You know there’s noise, but you can’t do much about it until you know what frequency it’s at.Take a look bycompleting the following steps:
The time domain analysis of the corrupted signal doesn’t show much. You should see something in the frequencydomain. Create a spectrogram using the following steps to see if there are any time varying components to thesignal.
iii.Plot the spectrogram with appropriate title and labels. Can you identify the frequency of the noise? Doesit match what you saw in the Fourier transform plot? (6 pts)
OK, now you’ve identified the frequency of the noise, it’s time to clean it up. Thing is, you’re not sure how much cleaning you should do. You don’t want to over-filter it, but you also need to be able to identify the signal you recorded. Try a range of filter orders by following these steps.
It’s Fall and just like the leaves are changing, so is Case. Download the logo from Canvas and use Matlab to revise it to be orange instead of blue. Hint: check what kind of image it is and use the information in one matrix to change the values of the others to set the blend of colors.
An important message has been recorded in the file Lab8Q3MSG.wav on Canvas, but someone botched the sampling rate. Play the signal and find the best sampling frequency to play it back at in order to determine the message. Use the disp function to write this message to the Command Window.
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