Introduction to Random Processes

Course content

Probability fundamentals; Random process characterization; Autocorrelation and autocovariance; Stationarity; Energy and power spectral densities; Gaussian processes; Filtering of random processes; Hilbert transform; Band-pass processes and low-pass equivalence; Markov chains: Convergence and transition probabilities; Steady-state probabilities; Counting processes and Poisson processes.