Gaussian Mean Filter in Python | Full Tutorial
• Introduction to the Digital Signal Process...
Learn how to implement a Gaussian mean filter in Python to remove noise and smooth signals efficiently. This step-by-step tutorial covers filter generation, zero padding, and edge handling for perfect signal recovery.
In this lecture, we implement a 1,000-point Gaussian mean filter in Python. We first generate a noiseless signal, add random noise to create a noisy signal, and then construct the Gaussian filter using the full width at half maximum (FWHM) parameter. Zero padding is applied to avoid edge effects, and the filter is convolved over the signal. Finally, the filtered signal is clipped to match the original length, producing a smooth and clean output.
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