6.262 Discrete Stochastic Processes

6.262 Discrete Stochastic Processes

25 Videos · Jan 15, 2011

About

Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance.

Videos

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01:16:26

Lecture 1: Introduction to Discrete Stochastic Processes and Probability Review

Robert G. Gallager

Feb 11, 2013

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7521 views

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01:23:45

Lecture 17: Countable-state Markov Chains

Robert G. Gallager

Feb 11, 2013

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2036 views

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01:18:16

Lecture 11: Renewals: Strong Law and Rewards

Robert G. Gallager

Feb 11, 2013

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2104 views

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01:23:37

Lecture 8: Markov Eigenvalues and Eigenvectors

Robert G. Gallager

Feb 11, 2013

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2410 views

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01:24:31

Lecture 5: Poisson Combining and Splitting

Robert G. Gallager

Feb 11, 2013

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2269 views

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01:17:13

Lecture 4: Poisson (The Perfect Arrival Process)

Robert G. Gallager

Feb 11, 2013

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2389 views

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01:19:16

Lecture 6: From Poisson to Markov

Mina Karzand

Feb 11, 2013

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3899 views

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01:21:16

Lecture 22: Random Walks and Thresholds

Robert G. Gallager

Feb 11, 2013

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2000 views

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01:21:52

Lecture 10: Renewals and the Strong Law of Large Numbers

Robert G. Gallager

Feb 11, 2013

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2229 views

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01:25:22

Lecture 21: Hypothesis Testing and Random Walks

Robert G. Gallager

Feb 11, 2013

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2442 views

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01:21:26

Lecture 25: Putting It All Together

Robert G. Gallager

Feb 11, 2013

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2131 views

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01:19:39

Lecture 16: Renewals and Countable-state Markov

Robert G. Gallager

Feb 11, 2013

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2100 views

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01:14:52

Lecture 13: Little, M/G/1, Ensemble Averages

Robert G. Gallager

Feb 11, 2013

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2243 views

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01:22:14

Lecture 19: Countable-state Markov Processes

Robert G. Gallager

Feb 11, 2013

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2052 views

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01:16:28

Lecture 18: Countable-state Markov Chains and Processes

Robert G. Gallager

Feb 11, 2013

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2280 views

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01:23:08

Lecture 20: Markov Processes and Random Walks

Robert G. Gallager

Feb 11, 2013

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2231 views

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01:21:27

Lecture 3: Law of Large Numbers, Convergence

Robert G. Gallager

Feb 11, 2013

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2330 views

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01:20:43

Lecture 24: Martingales: Stopping and Converging

Robert G. Gallager

Feb 11, 2013

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2315 views

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01:23:35

Lecture 9: Markov Rewards and Dynamic Programming

Robert G. Gallager

Feb 11, 2013

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2400 views

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01:08:19

Lecture 2: More Review; The Bernoulli Process

Robert G. Gallager

Feb 11, 2013

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3176 views

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01:19:18

Lecture 14: Review

Robert G. Gallager

Feb 11, 2013

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1919 views

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01:15:43

Lecture 15: The Last Renewal

Robert G. Gallager

Feb 11, 2013

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2085 views

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01:22:39

Lecture 23: Martingales (Plain, Sub, and Super)

Robert G. Gallager

Feb 11, 2013

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2248 views

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01:26:21

Lecture 12: Renewal Rewards, Stopping Trials, and Wald's Inequality

Robert G. Gallager

Feb 11, 2013

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2119 views

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55:33

Lecture 7: Finite-state Markov Chains; The Matrix Approach

Shan-Yuan Ho

Feb 11, 2013

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3440 views