Continuous-Time Markov Chains: Birth and Death Processes

Related lectures (29)

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Explores hitting times in Markov chains through various examples and scenarios.

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

Covers examples of absorbing Markov chains in discrete time.

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

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

Covers mathematical tools for communication systems and data science, including information theory and signal processing.

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

Explores conditional probability, Bayes' theorem, and prediction decomposition for informed decision-making.

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

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.