Discrete Stochastic Processes
Discrete Stochastic Processes
Robert Gallagher - MIT
1. Introduction & Probability Review
2. More Review: The Bernoulli Process
3. Law of Large Numbers, Convergence
4. Poisson (The Arrival Process)
5. Poisson Combining & Splitting
6. From Poisson to Markov
7. Finite-state Markov Chains, The Matrix Approach
8. Markov Eigenvalues & Eigenvectors
9. Markov Rewards & Dynamic Processing
10. Renewals & The Strong Law of Large Numbers
11. Renewals: Strong Laws & Rewards
12. Renewal Rewards, Stopping Trials, and Wald's Inequality
13. Little M/G/1, Ensemble Averages
14. Review
15. The Last Renewal
16. Renewals & Countable-state Markov
17. Countable-state Markov Assumptions
18. Countable-state Markov Chains & Processes
19. Countable-state Markov Processes
20. Markov Processes & Random Walks
21. Hypothesis Testing & Random Walks
22. Random Walks & Thresholds
23. Martingales (Plain, Sub, Super)
24. Martingales: Stopping & Converging
25. Putting it All Together