Markov Chains: Hitting Probabilities

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Related lectures (31)

Markov Chains Decomposition

Covers Markov chains decomposition, LLN proof, Inventory Model application, and average costs.

Stochastic Processes: Markov Chains

Covers stochastic processes, focusing on Markov chains and their applications in real-world scenarios.

Markov Chains: Applications and Coupled Chains

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

Markov Chains: Transition Densities

Covers Markov processes, transition densities, and distribution conditional on information, discussing classification of states and stationary distributions.

Markov Chains: Properties and Expectations

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

Discrete-Time Markov Chains: Definitions

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

Stochastic Models for Communications: Discrete-Time Markov Chains - First Passage Time

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

Stochastic Models for Communications: Discrete-Time Markov Chains - Absorption Time

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

Markov Chains: Recurrence and Transience

Explores first passage times, strong Markov property, and state recurrence/transience in Markov chains.

Probability Inequalities

Explores probability inequalities, convergence types, and moment generating functions for distribution approximation.

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