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Electronics & Communication Engineering
Signal Detection and Estimation Theory (Web)
Syllabus
Co-ordinated by :
IIT Guwahati
Available from :
2009-12-31
Lec :
1
Modules / Lectures
Signal Detection and Estimation Theory
Introduction to Detection and Estimation
Classical Unbiased Estimation and Bounds
Module1 Outline
Classical Unbiased Estimator
Bound and Fisher Information
CRLB for Transformed Parameter
CRLB for General Case
Linear Model and Applications
General Linear Model
General MVU Estimation
Module2 Outline
Sufficient Statistics
Determination of MVUE
Linear Unbiased Estimator
Maximum Likelihood Estimation (MLE)
Module3 Outline
Maximum Likelihood Estimation
MLE in General Cases
Properties of MLE
Least Square Estimation
Module4 Outline
Least Squares Estimation
Linear LSE
LSE: Geometrical Interpretation
Constrained LSE
Bayesian Estimation
Module5 Outline
Bayesian Estimation
Properties of Bayesian Estimator
General Bayesian Estimator
Estimation of Signals
Module6 Outline
Linear Bayesian Estimator
Wiener Smoother
Wiener Filter
Wiener Predictor
Detection Theory
Module7 Outline
Hypothesis Testing
Gauss-Gauss Detection Problem
Bayesian Detector
Minimax Detector
Multiple Hypothesis Testing
Bayesian Composite Hypothesis Testing
Generalized Likelihood Ratio Test
Non-Parametric Detection
Module8 Outline
Non-Parametric Detection: Sign Detector
Sequential Detection
Detection of Deterministic Signals in White Gaussian Noise
Module9 Outline
Replica-Correlator Detector
Properties of Matched Filter
Computation of Performance
Generalized Matched Filter
Signal Detection in Colored Noise
Detection and Linear Model
Detection of Random Signals in White Gaussian Noise
Module10 Outline
Energy Detector
Linear Model and Generalized Gaussian Detection
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