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

(25 Lectures Available)

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
  • 14. Review (M-I-T)
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

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