| S# |
Lecture |
Course |
Institute |
Instructor |
Discipline |
| 1 |
1. Introduction and Probability Review (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 2 |
10. Renewals and the Strong Law of Large Numbers (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 3 |
11. Renewals: Strong Law and Rewards (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 4 |
12. Renewal Rewards, Stopping Trials, and Wald's Inequality (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 5 |
13. Little, M/G/1, Ensemble Averages (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 6 |
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 7 |
15. The Last Renewal (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 8 |
16. Renewals and Countable-state Markov (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 9 |
17. Countable-state Markov Chains (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 10 |
18. Countable-state Markov Chains and Processes (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 11 |
19. Countable-state Markov Processes (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 12 |
2. More Review; The Bernoulli Process (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 13 |
20. Markov Processes and Random Walks (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 14 |
21. Hypothesis Testing and Random Walks (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 15 |
22. Random Walks and Thresholds (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 16 |
23. Martingales (Plain, Sub, and Super) (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 17 |
24. Martingales: Stopping and Converging (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 18 |
25. Putting It All Together (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 19 |
3. Law of Large Numbers, Convergence (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 20 |
4. Poisson (the Perfect Arrival Process) (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 21 |
5. Poisson Combining and Splitting (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 22 |
6. From Poisson to Markov (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 23 |
7. Finite-state Markov Chains; The Matrix Approach (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 24 |
8. Markov Eigenvalues and Eigenvectors (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
| 25 |
9. Markov Rewards and Dynamic Programming (M-I-T)
|
Discrete Stochastic Processes, Spring 2011 (M-I-T)
|
MIT
|
Prof. Robert Gallager
|
Applied Sciences
|
