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EECS 965 Course Schedule

Spring 2013


Detailed Schedule

Date Topic Assignment
01/22/2013 Lecture 1: course objective and review of probability
01/24/2013 Lecture 2: review of vector space and matrix analysis
01/29/2013 Lecture 3: introduction to statistical signal processing
01/31/2013 Lecture 4: binary hypothesis testing
02/05/2013 Lecture 5: Bayesian hypothesis testing and Neyman-Pearson hypothesis testingHomework 1 is assigned.
02/07/2013 Lecture 6: minimum variance unbiased estimation
02/12/2013 Lecture 7: Cramer-Rao lower bound (CRLB)Homework 1 is due, Homework 2 is assigned.
02/14/2013 Lecture 8: general CRLB for singlas in white Gaussian noise
02/19/2013 Lecture 9: linear models Homework 2 is due, Homework 3 is assigned.
02/28/2013 Lecture 10: system identification problem Homework 3 is due.
03/05/2013 Lecture 11: general minimum variance unbiased estimation
03/07/2013 Lecture 12: best linear unbiased estimator (BLUE)
03/12/2013 Lecture 13: maximum likelihood estimation (MLE)
03/14/2013 Lecture 14: least square estimation (LSE)
03/26/2013 Lecture 15: geometric intepretation, order-recursive and sequential LSE Homework 4 is assigned.
03/28/2013 Lecture 16: constrained LSE and nonlinear LSE
04/02/2013 Lecture 17: methods of moments Homework 4 is due.
04/04/2013 Lecture 18: review of classic estimation
04/09/2013 Mid-term exam.
04/11/2013 Lecture 19: Bayesian estimation
kucourses/eecs965/schedules13.txt · Last modified: 2017/09/07 10:31 by lingjialiu