Introduction to Signal Denoising in Python

https://www.youtube.com/watch?v=DCOqVC34o94&list=PLLlTVphLQsuMO2HsKm9I72gFcuBFlBSP6&index=1 In this video, we explore signal denoising, a crucial step in digital signal processing to recover clean signals from noisy data. Learn how moving average, Gaussian mean, and median filters help remove noise effectively while preserving the signal’s structure. We begin with the moving average filter, which averages values across a sliding window to smooth out noise. Next, the Gaussian mean filter applies a weighted averaging method based on the Gaussian distribution, maintaining the signal’s shape. Finally, the median filter, a non-linear filter, excels at removing spike-like or impulse noise without blurring edges. By the end of this tutorial, you will understand how to select the right filter depending on the type of noise affecting your signals.