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Home » Applied Sciences » Engineering » Discrete Stochastic Processes, Spring 2011 (M-I-T) » 16. Renewals and Countable-state Markov (M-I-T)

16. Renewals and Countable-state Markov (M-I-T)

Course:Discrete Stochastic Processes, Spring 2011 (M-I-T)
Discipline:Applied Sciences
Institute:MIT
Instructor(s): Prof. Robert Gallager
Level:Undergraduate

Discrete Stochastic Processes, Spring 2011 (M-I-T)

1. Introduction and Probability Review (M-I-T)
10. Renewals and the Strong Law of Large Numbers (M-I-T)
11. Renewals: Strong Law and Rewards (M-I-T)
12. Renewal Rewards, Stopping Trials, and Wald's Inequality (M-I-T)
13. Little, M/G/1, Ensemble Averages (M-I-T)
14. Review (M-I-T)
15. The Last Renewal (M-I-T)
16. Renewals and Countable-state Markov (M-I-T)
17. Countable-state Markov Chains (M-I-T)
18. Countable-state Markov Chains and Processes (M-I-T)
19. Countable-state Markov Processes (M-I-T)
2. More Review; The Bernoulli Process (M-I-T)
20. Markov Processes and Random Walks (M-I-T)
21. Hypothesis Testing and Random Walks (M-I-T)
22. Random Walks and Thresholds (M-I-T)
23. Martingales (Plain, Sub, and Super) (M-I-T)
24. Martingales: Stopping and Converging (M-I-T)
25. Putting It All Together (M-I-T)
3. Law of Large Numbers, Convergence (M-I-T)
4. Poisson (the Perfect Arrival Process) (M-I-T)

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