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HomeMIT 6.262 Discrete Stochastic Processes, Spring 2011Lecture 7: Finite-state Markov Chains; The Matrix Approach
MIT 6.262 Discrete Stochastic Processes, Spring 2011
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Lecture 7: Finite-state Markov Chains; The Matrix Approach
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Lecture 8: Markov Eigenvalues and Eigenvectors
Description: The transition matrix approach to finite-state Markov chains is developed in this lecture. The powers of the transition matrix are analyzed to understand steady-state behavior.
(Courtesy of Shan-Yuan Ho. Used with permission.)
Instructor: Shan-Yuan Ho
