**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**

Chapters 1-14 from the textbook.

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

**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