Instructor
Srikrishna Bhashyam
Office: NAC 343
Phone: 2257 4439
Pre-requisites
Probability and Random Processes.
Textbook
[1] S. M. Kay, "Fundamentals of Statistical Signal Processing: Estimation Theory," Prentice Hall, 1993.
Course Content Classical estimation: Minimum variance unbiased estimation, Cramer-Rao lower bound, Best linear unbiased estimators, Maximum likelihood estimation, Least squares, Method of moments.
Bayesian estimation: Minimum mean square error estimation, Maximum a posteriori estimation, Linear minimum mean square estimation, Kalman filters
Chapters 1-14 from the textbook.
References
[1] H. L. Van Trees, "Detection, Estimation, and Modulation Theory, Part I," John Wiley, 1968.
[2] H. V. Poor, "An Introduction to Signal Detection and Estimation," Springer, Second Edition, 1998.
Problem Sets
Evaluation
Lecture summary -- 10%
Quiz 1 (20%) -- Feb 17, 2022
Quiz 2 (20%) -- Mar 23, 2022
Final (50%) -- May 11, 2022