Topics Covered

  1. Introduction to Probability Theory and Random Variables2 weeks
  2. Joint and Conditional Distributions, Conditional Expectation, Limit Theorems2 weeks
  3. Static Estimation: MLE, MAP, MMSE, Principle of Orthogonality, Linear MSE2 weeks
  4. Dynamic Estimation: Kalman Filter2 weeks
  5. System Identification2 weeks
  6. Case Study1 week
  7. Optional: Stochastic Processes — Stationarity, Ergodicity, Second-order Theory2 weeks

Reference Materials

  1. Random Processes for Engineers by Bruce Hajek. [Free preprint]
  2. Stochastic Processes, Estimation and Control by Jason Speyer and Walter Chung. SIAM, 2008. [Link]
  3. Probability and Random Processes by Geoffrey Grimmett and David Stirzaker. [Link]
  4. Stochastic Systems: Estimation, Identification, and Adaptive Control by P. R. Kumar and Pravin Varaiya. SIAM. [Link]
  5. System Identification: Theory for the User by Lennart Ljung. Standard textbook for system identification. [Link]

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