Discrete-time Markov Chains and Poisson Processes DJ9GZ69RSG
| URI | m2://res/DJ9GZ69RSG |
|---|---|
| Kind | course |
| Creators | Ayon Ganguly Prof. Subhamay Saha (instructor) |
| Date | 2022-01-11 |
| MSC | 60-XX |
| Scope | in |
| Ids | course 0022nd079:111103158 |
Expressions
e1: edition
| Language | en |
|---|---|
| Date | 2022-01-11 |
- m1: page, IIT Guwahati (record). nptel 111103158
- m2: page, 2022-01-11 (record). nptel 111103158
Contents
- part 1: Week 1: Introduction to Discrete-time Markov Chains
- session 1: Lec 1: Review of Basic Probability I
- session 2: Lec 2: Review of Basic Probability II
- session 3: Lec 3: Review of Basic Probability III
- session 4: Lec 4: Stochastic Processes
- session 5: Lec 5: Definition of Markov Chain and Transition Probabilities
- part 2: Week 2: Chapman-Kolmogorov Equations and Communication
- session 6: Lec 6: Markov Property and Chapman-Kolmogorov Equations
- session 7: Lec 7: Chapman-Kolmogorov Equations: Examples
- session 8: Lec 8: Accessibility and Communication of States
- part 3: Week 3: Hitting Times and Strong Markov Property
- session 9: Lec 9: Hitting Time I
- session 10: Lec 10: Hitting Time II
- session 11: Lec 11: Hitting Time III
- session 12: Lec 12: Strong Markov Property
- part 4: Week 4: Classification of States
- session 13: Lec 13: Passage Time and Excursion
- session 14: Lec 14: Number of Visits
- session 15: Lec 15: Class Property
- session 16: Lec 16: Transience and Recurrence of Random Walks
- part 5: Week 5: Stationary Distribution
- session 17: Lec 17: Stationary Distribution I
- session 18: Lec 18: Stationary Distribution II
- session 19: Lec 19: Stationary Distribution III
- part 6: Week 6: Limit Theorems & Time Reversibility
- session 20: Lec 20: Limit Theorems I
- session 21: Lec 21: Limit Theorems II
- session 22: Lec 22: Some Problems I
- session 23: Lec 23: Some Problems II
- session 24: Lec 24: Time Reversibility
- part 7: Week 7: Exponential Distribution and Poisson Processes
- session 25: Lec 25: Properties of Exponential Distribution
- session 26: Lec 26: Some Problems
- session 27: Lec 27: Order Statistics
- session 28: Lec 28: Poisson Processes
- part 8: Week 8: Poisson Processes
- session 29: Lec 29: Poisson Thinning I
- session 30: Lec 30: Poisson Thinning II
- session 31: Lec 31: Conditional Arrival Times
- session 32: Lec 32: Independent Poisson Processes
- session 33: Lec 33: Some Problems
- session 34: Lec 34: Compound Poisson Processes
- part 9: Live Session
- session 35: Live Session 15-03-2022
Catalogue records
- nptel: 111103158 (manifestation)
- nptel_video: 111103158 (manifestation)