Continuous-Time Markov Chains: Kolmogorov Equations

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Covers the theory and applications of Markov chains in modeling random phenomena and decision-making under uncertainty.

Explores discrete-time Markov chains, emphasizing the concept of first passage time in communication systems.

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

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

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

Explores examples of absorbing chains in discrete-time Markov chains, focusing on transition probabilities.

Explores the asymptotic behavior of continuous-time Markov chains and their convergence properties.

Covers reversible discrete-time Markov chains in communication models.

Explores invariant distributions, recurrent states, and convergence in Markov chains, including practical applications like PageRank in Google.

Covers continuous-time Markov chains, focusing on reversible chains and their properties.