Sampling: Signal Reconstruction and Aliasing

This lecture covers the importance of sampling, the sampling theorem, signal reconstruction, and aliasing in the context of digital representation. It explains the process of sampling complex exponentials and provides examples of signal reconstruction from samples. The lecture also delves into impulse train sampling, modeling sampling as multiplication by an impulse train, and deriving the sampling theorem for continuous-time signals. Additionally, it discusses the reconstruction of signals using low-pass filters and the implications of band-limited signals in the sampling process.