Python-Signal-Processing

A college assignment where a frequency analysis had to be performed using the Fast Fourier Transform, a exemplary algorithm used in Digital Signal Processing

Modules/Packages used:

1. Scipy.fft
2. Scipy.io.wavfile
3. Numpy
4. Matplotlib.pyplot

Assignment Details:

Generate 2 sine waves.
Synthesize the waves together.
Transform using FFT to read frequency data.
Analyze and remove a desired synthesized frequency.
Normalize audio and save clean sine wave file.

Thorough Explanation:

Generate 2 sine waves, each from different frequencies. In this assignment: 432Hz and the other 4000Hz.
Synthesize waves together and create a more complex sine wave. Once synthesized, a normalization had to take place.
When normalized the audio has the ability to be visualized within the time domain and be saved locally as a .wav file.
The following step, transform the audio to the frequency domain using the FFT algorithm.
Once data has been transformed, another visualization can be done and see the 2 given frequencies on the graph.
Analyze the frequency data and remove the desired frequency.
Once desired frequency is removed, the data has to be transformed/reverted back into the time domain.
Again the data has the ability to be visualized, this time if graphed, you will only notice the none-removed sine wave.
When audio is finally transformed back into time domain, the audio is normalized ready to be played using an audio player.