University of California, Santa Barbara
Department of Electrical and Computer Engineering

Optimal Estimation and Filtering

ECE 240A - Winter 2010

Instructor: Professor John J. Shynk

Schedule: Tuesday and Thursday
2:00 - 3:50 p.m.
Phelps 1437

 

Announcements:

Office Hours:

Tuesday and Thursday 4:00 - 5:00 p.m.

Course Information:

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.

Grading:

Homework Problems (weekly), 15%
Midterm Exam (open book), 35% (Thursday, February 11, 2:00 - 3:50 p.m.)
Final Exam (open book), 50% (Wednesday, March 17, 4:00 - 7:00 p.m.)

Prerequisites:

Probability and random processes (ECE 139 and 140 or equivalent),
linear algebra (ECE 130C or equivalent),
(ECE 210A and 235 are not required).

Required Text:

Mendel, Lessons in Estimation Theory for Signal Processing, Commnications, and Control,
Prentice-Hall PTR, 1995 (2nd Edition)

Lecture Handouts:

 

Current ECE Courses || Electrical and Computer Engineering || College of Engineering

Last Updated: March 15, 2010