Sampling Theorem: Illustration

This lecture covers the sampling theorem, which states that a signal can be perfectly reconstructed from its samples if the sampling frequency is greater than twice the maximum signal frequency. Through graphical illustrations, the reconstruction of a pure sinusoidal signal is demonstrated, showing the importance of the sampling frequency in achieving accurate reconstruction. The lecture also explores the effects of under-sampling, known as the stroboscopic effect, and presents solutions to mitigate this phenomenon, such as filtering the signal before sampling. Theoretical demonstrations and examples help solidify the concepts behind the sampling theorem and its practical implications in signal processing and telecommunications.