DETECTION AND ESTIMATION THEORY

Discrete representation of deterministic and random signals.
 
Detection theory--Statistic model for detection. MAP criterion. Detection in the presence of additive white Gaussian noise. Sufficient statistics. Matched filter. Detection in the presence of additive Gaussian colored noise: reversibility theorem. Detection in the presence of random parameters.
 
Estimation theory--Statistic model for estimation. Estimation of deterministic parameters: ML criterion. Estimation of stochastic parameters: Bayes criterion. Cramer-Rao inequality. Minimum mean square linear estimation. Wiener filter. Prediction. Kalman filter.