Continuous-Time Markov Chains: Definitions and State Probabilities

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Covers examples of absorbing Markov chains in discrete time.

Covers the definitions and state probabilities of continuous-time Markov chains.

Discusses discrete-time Markov chains and absorption time in communication systems.

Explores a first-order Markov model using a sunny-rainy source example, demonstrating how past events influence future outcomes.

Explores Markov chains' properties, expectations, and recurrence in Poisson processes.

Explores birth and death chains, hitting probabilities, and expected game durations in Markov chains.

Explores the Bonus Malus system for insurance premiums and Markov chain transition probabilities.

Covers the interpretation of the Lindblad equation and its unitary part in quantum gases.

Covers the criterion for recurrence in infinite chains based on the expected number of visits in a state.

Explores Markov chain games, hitting probabilities, and expected hitting times in a target set.