محتويات مقرر Detection and Estimation Theory
Course Content :-
- Part I Detection Theory:Hypothesis testing: Likelihood Ratio Test, Bayes’ Criterion, Minimax Criterion, Neyman-Pearson Criterion, Sufficient Statistics, Performance Evaluation.
- Multiple hypothesis testing.
- Composite hypothesis testing.
- Sequential detection.
- Detection of known signals in white noise.
- Detection of known signals in colored noise.
- Detection of signals with unknown parameters.
- Non-parametric detection.
- Part II Estimation Theory: Bayesian parameter estimation.
- Non-Bayesian parameter estimation.
- Properties of estimators: sufficient statistics, bias, consistency, efficiency, Cramer-Rao bounds.
- Linear Mean-Square Estimation.
- Waveform Estimation.
