1. Read in the horn signal, and use the sampling rate fs that you read in to create a time vector of length 100ms. Define the fundamental frequency to be fo = 335Hz. Create a signal that is a sinusoid at that frequency, and save it as a wav file. 2. Create a vector (or two) to characterize a using: ak: [2688, 1900, 316, 178, 78, 38] Zak[-1.73,-1.45, 2.36, 2.30, -2.30, 1.13] assuming a = 0 and the first element of the vectors correspond to a₁. Use the function you created in part 1 to synthesize a signal, with fs and fo above, and save it as a wav file. 2 3. Plot the 100ms section of the original file starting at 200ms with a plot of the synthesized signal in a 2x1 plot. 4. Play the original file, the single tone, and the 6-tone approximation in series. Report discussion: The approximation does not sound quite like the original signal and the plot should look pretty different. The difference in sound is in part due to multiple factors, including the truncated approximation, imperfect estimate of the parameters, and the fact that the original signal is not perfectly periodic. Try adjusting some parameters and determine what you think is the main source of distortion.

Computer Networking: A Top-Down Approach (7th Edition)
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Pls use python. The horn file can be substituted with any wav file.

1. Read in the horn signal, and use the sampling rate fs that you read in to create a time vector of length
100ms. Define the fundamental frequency to be fo = 335Hz. Create a signal that is a sinusoid at that
frequency, and save it as a wav file.
2. Create a vector (or two) to characterize a using:
ak
Zak
[2688, 1900, 316, 178, 78, 38]
: [-1.73, -1.45, 2.36, 2.30, -2.30, 1.13]
assuming a = 0 and the first element of the vectors correspond to a₁. Use the function you created
in part 1 to synthesize a signal, with fs and fo above, and save it as a wav file.
2
3. Plot the 100ms section of the original file starting at 200ms with a plot of the synthesized signal in a
2x1 plot.
4. Play the original file, the single tone, and the 6-tone approximation in series.
Report discussion: The approximation does not sound quite like the original signal and the plot should
look pretty different. The difference in sound is in part due to multiple factors, including the truncated
approximation, imperfect estimate of the parameters, and the fact that the original signal is not perfectly
periodic. Try adjusting some parameters and determine what you think is the main source of distortion.
Transcribed Image Text:1. Read in the horn signal, and use the sampling rate fs that you read in to create a time vector of length 100ms. Define the fundamental frequency to be fo = 335Hz. Create a signal that is a sinusoid at that frequency, and save it as a wav file. 2. Create a vector (or two) to characterize a using: ak Zak [2688, 1900, 316, 178, 78, 38] : [-1.73, -1.45, 2.36, 2.30, -2.30, 1.13] assuming a = 0 and the first element of the vectors correspond to a₁. Use the function you created in part 1 to synthesize a signal, with fs and fo above, and save it as a wav file. 2 3. Plot the 100ms section of the original file starting at 200ms with a plot of the synthesized signal in a 2x1 plot. 4. Play the original file, the single tone, and the 6-tone approximation in series. Report discussion: The approximation does not sound quite like the original signal and the plot should look pretty different. The difference in sound is in part due to multiple factors, including the truncated approximation, imperfect estimate of the parameters, and the fact that the original signal is not perfectly periodic. Try adjusting some parameters and determine what you think is the main source of distortion.
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