Covers examples of signal processing, analog signal processing, continuous amplitude modulation, image processing, compression, micro-systems, and medical electronics.
Introduces mathematical tools for communication systems and data science, focusing on stochastic processes and preparing students for advanced courses.
Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.
Covers the concepts of sampling and reconstruction in signal processing, emphasizing the importance of sampling frequency and reconstruction techniques.
