Optimal estimation concepts and theory (minimum variance, least squares, and maximum likelihood estimation), optimal recursive algorithms for discrete- and continuous-time filtering of noisy signals and data. Wiener and Kalman filters, stability of recursive optimal filtering algorithms, modeling errors in recursive filters.
4
UnitsLetter
Grading1, 2, 3
PasstimeNone
Level LimitEngineering
CollegeLecture
Nah, I'd win
fine, but after the final she made us turn in our cheatsheets. she did not warn us about this in advance, so i was really disappointed because i spent lots of time making mine and it is gone now. not sure what the purpose of this was, seems really stupid
Pretty good professor. Recorded all lectures, The only problem I had with the class was the exams. Both midterms were only 2 questions, meaning if you made a single mistake you were absolutely cooked. They were easy, but I feel like that format of an exam is a terrible way to assess a student's knowledge.
Alizadeh is a very nice and patient professor. While I did not like the actual content of the course, she made it clear with what she expected in all our work. One midterm was not very fair, but overall it was understandable. She records lectures, posts empty and annotated slides, is technical and conceptual, and is responsible.
Took online during COVID. The class material puts together the entire 10 series. Detailed & well-organized recorded lectures and slides really helped study. Exams require a good grasp of the design instead of straight-out circuit solving.
She is a new professor. She always tried her best, but when she explained concepts, she made me confused(She made a lot of mistakes in the lectures or problem solving for the exams). Personally, I thought 10B was easier.