In python please!!. Thanks in advance.
Posted: Fri May 20, 2022 4:38 pm
In python please!!. Thanks in advance.
Problem Implement the Discrete Fourier Transform using your preferred programming language. Make your implementation generic to accept any number of points for the input signal. Use your DFT implementation to show the frequency spectrum of some signals as described below. n Specifications 1. Generate samples and plot the following sequence: x[n] = (sin(2 n n / 40) + 2 sin(2 n n / 16)) exp(-((n-128) / 64)2) 2. Take the 256 point DFT of this signal. Plot the real and imaginary parts. [1pt] 3. Convert the frequency spectrum into polar form. Plot the magnitude and phase parts. [1pt] 4. Repeat step 3 for the 128-DFT. [1pt] 5. Have you noticed any differences between the frequency spectrum of 128, and 256 points? [1pt] 6. Take the Inverse DFT of 256 DFT spectrum. Compare the resulting time domain signal with the original? Are they identical? [1pt] 7. Generate a 1 sec digital signal from your microphone pronouncing your name and save it as an uncompressed audio file. You can use 'Audacity' or any other external software to generate the audio file. 8. Apply the DFT and inverse DFT after selecting a suitable sampling rate. Compare the original audio and the one resulted from inverse DFT by listening to both. [1pt]
Problem Implement the Discrete Fourier Transform using your preferred programming language. Make your implementation generic to accept any number of points for the input signal. Use your DFT implementation to show the frequency spectrum of some signals as described below. n Specifications 1. Generate samples and plot the following sequence: x[n] = (sin(2 n n / 40) + 2 sin(2 n n / 16)) exp(-((n-128) / 64)2) 2. Take the 256 point DFT of this signal. Plot the real and imaginary parts. [1pt] 3. Convert the frequency spectrum into polar form. Plot the magnitude and phase parts. [1pt] 4. Repeat step 3 for the 128-DFT. [1pt] 5. Have you noticed any differences between the frequency spectrum of 128, and 256 points? [1pt] 6. Take the Inverse DFT of 256 DFT spectrum. Compare the resulting time domain signal with the original? Are they identical? [1pt] 7. Generate a 1 sec digital signal from your microphone pronouncing your name and save it as an uncompressed audio file. You can use 'Audacity' or any other external software to generate the audio file. 8. Apply the DFT and inverse DFT after selecting a suitable sampling rate. Compare the original audio and the one resulted from inverse DFT by listening to both. [1pt]