EE5112 Detection Theory (Jan-May 2021)

Instructor

Srikrishna Bhashyam
Office: NAC1 343
Phone: 2257 4439

Pre-requisites
EE5110/EE3110 Probability Foundations for Electrical Engineers

Course Content

Hypothesis Testing: Bayesian hypothesis testing, Minimax hypothesis testing, Neyman-Pearson hypothesis testing, Composite hypothesis testing

Signal Detection: Deterministic signals in independent noise, Deterministic signals in (non-i.i.d.) Gaussian noise, Detection of signals with random parameters, Performance

Sequential detection: Sequential Probability Ratio Test

Nonparametric Detection, Robust detection

Textbook

[1] H. V. Poor, "An Introduction to Signal Detection and Estimation," Springer, Second Edition, 1998.


References

[1] S. M. Kay, "Fundamentals of Statistical Signal Processing: Detection Theory," Prentice Hall, 1998.
[2] P. Moulin, V. V. Veeravalli, "Statistical Inference for Engineers and Data Scientists," Cambridge University Press, 2019.
[3] H. L. Van Trees, "Detection, Estimation, and Modulation Theory, Part I," John Wiley, 1968.


Lecture Notes
2018 Lecture Notes


Evaluation
Lecture Summary (10%)
Quiz 1 (20%)
Quiz 2 (20%)
Final (50%)


Moodle
Login here