Schedule
- Class: Tu, Th, 4:15pm - 5:30pm, Room 550-553R
- Sanjay's office hours: Wed, 2:00pm - 3:30pm
- Review session: Mondays, 6-7pm, 100-100K
- CA's Office hours: Fridays, 1-3pm, Durand 272
Lecture Notes
- 1. Introduction (ps, pdf, 2ps, 2pdf)
- 2. Probability on finite sets (ps, pdf, 2ps, 2pdf)
- 3. Random variables (ps, pdf, 2ps, 2pdf)
- 4. Estimation and prediction (ps, pdf, 2ps, 2pdf)
- 5. Random vectors (ps, pdf, 2ps, 2pdf)
- 6. Classification (ps, pdf, 2ps, 2pdf)
- 7. Continuous random variables (ps, pdf, 2ps, 2pdf)
- 8. Continuous random vectors (ps, pdf, 2ps, 2pdf)
- 9. Conditional density (ps, pdf, 2ps, 2pdf)
- 10. MMSE etimation (ps, pdf, 2ps, 2pdf)
- 11. The linear model (ps, pdf, 2ps, 2pdf)
- 12. Linear regression (ps, pdf, 2ps, 2pdf)
- 13. Recursive estimation (ps, pdf, 2ps, 2pdf)
- 14. The Kalman filter (ps, pdf, 2ps, 2pdf)
Homework
- Homework 1 (ps, pdf)
- Homework 1 solutions (ps, pdf)
- Homework 2 (ps, pdf)
- Homework 2 solutions (ps, pdf)
- Homework 3 (ps, pdf)
- Homework 3 solutions (ps, pdf)
- Homework 4 (ps, pdf)
- Homework 4 solutions (ps, pdf)
- Homework 5 (ps, pdf)
- Homework 5 solutions (ps, pdf)
- Homework 6 (ps, pdf)
- Homework 6 solutions (ps, pdf)
- Homework 7 (ps, pdf)
- Last year's midterm (ps, pdf)
- Last year's midterm solutions (ps, pdf)
- Last year's final (ps, pdf)
- Last year's final solutions (ps, pdf)
Matlab