Random Processes

Collection type: Course

Course by: Nick Kingsbury

Probability Distributions

• Aims and Motivation for the Course
• Probability Distributions
• Conditional Probabilities and Bayes' Rule
• Joint and Conditional cdfs and pdfs

Random Vectors, Signals and Functions

• Random Vectors
• Random Signals
• Approximation Formulae for the Gaussian Error Integral, Q(x)

Expectations, Moments, and Characteristic Functions

• Expectation
• Important Examples of Expectation
• Sums of Random Variables
• Characteristic Functions

Correlation Functions and Power Spectra

• Random Processes
• Correlation and Covariance
• Stationarity
• Ergodicity
• Spectral Properties of Random Signals
• White and Coloured Processes