Markov Chains: Communicating Classes

This lecture covers the identification of communicating classes in Markov chains, distinguishing between transient and recurrent classes. The instructor explains the concepts using examples of Markov chains with different transition probability matrices. The lecture also delves into the properties of these classes, such as recurrence and transience, providing insights into the behavior of the chains over time. Additionally, the lecture explores the stationary distribution of Markov chains and the significance of doubly stochastic transition probability matrices. Various exercises are presented to reinforce the understanding of the discussed concepts.