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
CollegeShe's ok. Homeworks aren't too bad, she records lectures, drops one homework, slightly adjusts your percentage towards the better exam. However, the exams that she gives are strange. The midterms have two problems: First problems are easy, second problem not so much. Final was pretty rough. It's like you expect a fair exam but don't, simultaneously
She's pretty good, recorded lectures, explained everything clearly. The midterms were pretty easy but also only consisted of two questions so you should be really careful to not make any mistakes. The only complaint I have is that the final was a pretty big step up in terms of difficulty compared to anything else we did in class so be ready
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.