Window Functions in DSP - From Theory to MATLAB

This video provides a clear and practical explanation of windowing and window functions in digital signal processing (DSP). We cover everything from the fundamental definition of windowing to its critical role in spectrum analysis. You’ll learn how windowing helps reduce spectral leakage, how different window functions behave, and why choosing the right window matters for accurate frequency-domain analysis.

We walk through the full theory of windowing — from infinite signals to finite signals, the time-domain multiplication and frequency-domain convolution, and the trade-off between main lobe width and sidelobe attenuation. Using MATLAB simulations, we demonstrate how different windows (Rectangular, Hamming, Hann, Blackman, and Chebyshev) affect both signals and their spectra.

You’ll see how windowing shapes the time-domain signal, modifies the frequency spectrum, and impacts signal processing applications like spectral estimation and digital filter design.

🚀 What you’ll learn in this video:
✅ What windowing is and why it’s needed in DSP
✅ How rectangular windows cause spectral leakage
✅ How smoother windows reduce sidelobes at the cost of frequency resolution
✅ Comparison of common window functions: Rectangular, Hamming, Hann, Blackman, Chebyshev
✅ MATLAB implementation of windowing step-by-step

⏱️ Chapters
0:00 – Introduction
0:16 – Windowing Fundamentals
2:12 – Popular Windows in DSP
3:26 – MATLAB: Window Functions Generation
4:30 – MATLAB: Windowing Effect on Signals
5:24 – MATLAB: Windowed Signal Spectra

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💻 Get the MATLAB Code Here: https://github.com/marwyp/WaveformAca...

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