• Estimation in signal processing. The mathematical estimation problem. Assessing estimator performance. Some notes to the reader. Minimum variance unbiased estimation. Cramer - Rao lower bound. Linear models. General minimum variance unbiased estimation. Best linear unbiased estimators. Maximum likelihood estimation. Least squares. Method of moments. The Bayesian philosophy. General Bayesian estimators. Linear Bayesian estimators. Kalman filters. Summary of estimators. Extensions for complex data and parameters.

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