Gaussian Mean Filter Explained for Signal Denoising

https://www.youtube.com/watch?v=DCOqVC34o94&list=PLLlTVphLQsuMO2HsKm9I72gFcuBFlBSP6&index=1 Learn how the Gaussian mean filter works to remove noise and smooth signals effectively. This tutorial covers the principles of Gaussian filtering, including kernel generation, full width at half maximum (FWHM), and edge handling for clean signal recovery. In this lecture, we explore the Gaussian mean filter, also known as the Gaussian kernel filter, for signal denoising. Unlike the moving average filter, the Gaussian filter is generated using the Gaussian equation and creates a smooth kernel. We explain how to apply this kernel to a noisy signal, address edge effects with zero padding, and clip the filtered signal to match the original length. The result is a perfectly smooth, denoised signal ready for further processing.