ENGIN 322: Probability & Random Processes

An introduction to probabilistic description (via the probability density function or distribution function) and statistical description (via the ensemble average, variance, etc.) of random signals as applied to the analysis of linear systems. Other topics include conditional probability, statistical independence, correlation, sampling theory, confidence intervals, hypothesis testing, stationary and ergodic processes, auto-correlation and cross-correlation functions, spectral density, and their interconnections.