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Hidden Markov Model Lecture #6. 2 Reminder: Finite State Markov Chain An integer time stochastic process, consisting of a domain D of m states {1,…,m} - ppt download
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What if time ran backwards? If X n, 0 ≤ n ≤ N is a Markov chain, what about Y n = X N-n ? If X n follows the stationary distribution,
Inequalities in Theorems of Ergodicity and Stability for Markov Chains with Common Phase Space. II | Theory of Probability & Its Applications
![Ole Peters on Twitter: "Birkhoff's ergodic theorem as a warning: probability theory throws away the dynamics (slide from https://t.co/wwap6U5Kvb, scribbles my own). https://t.co/QKYvnDEM8X" / Twitter Ole Peters on Twitter: "Birkhoff's ergodic theorem as a warning: probability theory throws away the dynamics (slide from https://t.co/wwap6U5Kvb, scribbles my own). https://t.co/QKYvnDEM8X" / Twitter](https://pbs.twimg.com/media/DM_7G-9WAAU5dQD.jpg:large)
Ole Peters on Twitter: "Birkhoff's ergodic theorem as a warning: probability theory throws away the dynamics (slide from https://t.co/wwap6U5Kvb, scribbles my own). https://t.co/QKYvnDEM8X" / Twitter
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