Analysis Seminar

Speaker: Robbie Robinson

Title: Stationary guassian Processes IV

Abstract: Stationary Gaussian processes are classical probabilistic models used in applications such as digital signal processing, machine learning and quantum mechanics. This is the second talk in this series.  In the first talk I set up the measure theoretic background for studying probability theory and stochastic processes, including a discussion the Kolmogorov consistency theorem.  In the second talk,  I will also describe classical random variables, and the special properties of Gaussian random variables that make Gaussian processes nice. We will discuss both the real and less well known complex cases