Catalog · Discrete Stochastic Processes Lecture 8 of 25 Lecture 8: Markov Eigenvalues and Eigenvectors ← Previous Lecture 7: Finite-state Markov Chains; The Matrix Approach Next → Lecture 9: Markov Rewards and Dynamic Programming ✓ Mark complete Materials Transcript (PDF) ↗ transcript