Course Details
Subject {L-T-P / C} : EC6504 : Estimation and Detection Theory { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Prof. Siddharth Deshmukh
Syllabus
Review of Gaussian Variables and Processes: Problem Formulation and Objective of Signal Detection and Signal Parameter Estimation in Discrete-Time Domain, Estimation of Signal Parameters: Minimum Variance Unbiased Estimation(MVUE), Fisher Information Matrix, Cramer-Rao Lower Bound, Linear Models, Generalized Minimum Variance Unbiased Estimation, Best Linear Unbiased Estimators (BLUE) Maximum Likelihood Estimation(MLE), Statistical Decision Theory: Neyman-Pearson Theorem, Receiver Operating Characteristics, Irrelevant Data, Minimum Probability of Error, Bayes Risk, Multiple Hypothesis Testing, Detection of Deterministic Signals: Matched Filter Detector and Its Performance Generalized Matched Filter Multiple Signals. Detection of Random Signals: Estimator-Correlator, Linear Model, General Gaussian Detection, Composite Hypothesis Testing and it’s approaches, Locally Most Powerful Detectors, Multiple Hypothesis Testings.
Course Objectives
- To build concepts on statistical signal processing
Course Outcomes
Students will have concepts for research on Digital Signal Processing, Communication, Information Theory, Detection Theory, Array Signal Processing, Radar, Sonar, Acoustic Signal Processing
Essential Reading
- S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Printice hall , Vol I 2009
- S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory, Printice hall , Vol II 2008
Supplementary Reading
- H V Poor, An Introduction to Signal Detection and Estimation, Springer , 2nd Edition 2008
- Harry L. Van Trees, Detection, Estimation and Modulation Theory, John Wiley & Sons , Part I 2002