Lower Bound on Total Variation Distance

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Covers stochastic models for communications, focusing on discrete-time Markov chains.

Covers hitting probabilities in Markov chains with disjoint subsets, the function h(i), theorems, proofs, and expected time to hit calculations.

Explains the proof of the ergodic theorem and the concept of positive-recurrence in Markov chains.

Presents a short proof of a conjecture by Erdös, exploring related questions and detailed proof of the proposition.

Covers Markov chains, coupled chains, and their applications, emphasizing the importance of irreducibility.

Explores ergodicity and stationary distribution in Markov chains, emphasizing convergence properties and unique distributions.

Covers the basic theory for continuous time Markov chains and discusses communication, hitting probabilities, recurrence, and transience.