Signals & Systems II: Complex Random Vectors and Stationarity

This lecture covers the analysis of complex random vectors in signal processing, focusing on statistics of order 1 and 2, optimization calculations of quadratic forms, and the estimation of linear parameters. It delves into the concept of stochastic processes, stationarity, ergodicity, and the distinction between stationary colored noise and speech signals. The importance of ergodic processes and the implications of ergodicity on statistical means are also discussed, along with the differences between continuous-time and discrete-time signals.