Lectures related to Discrete-Time Markov Chains: Definitions

Discrete-Time Markov Chains: Definitions

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

Markov Chains: Definitions and State Probabilities

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

Birth & Death Chains: Analysis & Probabilities

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

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

Explores discrete-time Markov chains, emphasizing first passage time probabilities and minimal solutions.

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

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

Markov Chains: Absorbing Classes

Explores Markov chains with absorbing classes through exercises on transition matrices and expected values.

Stochastic Models: Absorbing Markov Chains Examples

Covers examples of absorbing Markov chains in discrete time.

Hidden Markov Models: Primer

Introduces Hidden Markov Models, explaining the basic problems and algorithms like Forward-Backward, Viterbi, and Baum-Welch, with a focus on Expectation-Maximization.

Stochastic Models for Communications

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

Probability & Stochastic Processes

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Sunny Rainy Source: Markov Model

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

Continuous-Time Markov Chains: Definitions and State Probabilities

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

Markov Chains: Theory and Applications

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

Lindblad equation

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

Bonus Malus System: Transition Probabilities

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

Continuous-Time Markov Chains: Definitions and State Probabilities

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

NISQ and IBM Q

Explores NISQ devices and IBM Q, covering noisy quantum circuits, qubit technologies, and quantum algorithm development.

Continuous-Time Markov Chains: Definitions and State Probabilities

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

Expected Number of Visits in State

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

Conditional Expectation: Grouping Lemma

Explores conditional expectation, the grouping lemma, and the law of large numbers.