Line 16: Line 16:
 
# [[Recurrent State and Transient State]]
 
# [[Recurrent State and Transient State]]
  
[[Theorem: Steady-State Vectors]]
+
[[Theorem: Steady-State Vectors / Stationary Distribution]]
 +
 
 +
[[Restrictions of Stationary Distribution]]
  
 
[[Applications of Markov Chains]]
 
[[Applications of Markov Chains]]

Revision as of 02:01, 6 December 2020

Markov Chains

Yi Li and Nicholas Fang

Table of Contents

Introduction and Historic Background

Basics of Markov Chains

  1. Transition Diagrams
  2. Transition Probability Matrix
  3. n-th Term Transition
  4. Python Demonstration

Classification of States

  1. Communication and Reducibility
  2. Periodicity of Markov Chains
  3. Recurrent State and Transient State

Theorem: Steady-State Vectors / Stationary Distribution

Restrictions of Stationary Distribution

Applications of Markov Chains

Markov Chain References and Additional Readings

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang