Introduces mathematical tools for communication systems and data science, focusing on stochastic processes and preparing students for advanced courses.
Covers the concepts of sampling and reconstruction in signal processing, emphasizing the importance of sampling frequency and reconstruction techniques.
Covers the Fourier transform, its properties, and applications in signal processing and differential equations, demonstrating its importance in mathematical analysis.
Covers fundamental concepts in electronics design, including Maxwell's equations, Kirchoff's equations, active components, PCB fabrication, impedance matching, and ADC architectures.
Explores Monte Carlo techniques for sampling and simulation, covering integration, importance sampling, ergodicity, equilibration, and Metropolis acceptance.