**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**

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