Chapter 13: Introduction to Stochastic Processes

Learning Objectives

• Define a stochastic process and distinguish continuous-time from discrete-time, continuous-valued from discrete-valued
• Characterize a process through its finite-dimensional distributions and sample paths
• State the definitions of strict-sense stationarity and wide-sense stationarity and explain their relationship
• Derive and apply the fundamental properties of autocorrelation and autocovariance functions
• Compute cross-correlation and cross-covariance for jointly WSS processes
• State the conditions under which time averages equal ensemble averages (ergodicity)
• Apply second-order statistics to classify and analyze random signals in communications