Discrete-Time Markov Chains: Reversible Chains

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Explores time reversal in stationary Markov chains and the concept of detailed balance conditions.

Covers reversible discrete-time Markov chains in stochastic communications, explaining stationarity and transition probabilities.

Covers reversible discrete-time Markov chains in communication models.

Explores reversibility and irreducibility in Markov chains, along with optimal decision-making policies.

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Covers Markov chains, focusing on reversibility, convergence, ergodicity, and applications.

Explores Markov chains and their applications in algorithms, focusing on user impatience and faithful sample generation.

Explores reversibility in Markov chains and its impact on the stationary distribution, highlighting the complexity of non-reversible chains.

Covers Markov chains and their applications in algorithms, focusing on Markov Chain Monte Carlo sampling and the Metropolis-Hastings algorithm.

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