Musical Expectancy: Modeling and Transitions

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

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

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Covers Markov Chain Monte Carlo examples and error estimation methods.

Covers Hidden Markov Models (HMM) for modeling time series data and decoding using the Viterbi Algorithm.

Explores Markov chains, Ising Model, Metropolis algorithm, and Glauber dynamics.

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

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Explores the relationship between melody and harmony in music.

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