1. Introduction. 2. Minimum Variance Unbiased Estimation. 3. Cramer-Rao Lower Bound. 4. Linear Models. 5. General Minimum Variance Unbiased Estimation. 6. Best Linear Unbiased Estimators. 7. Maximum Likelihood Estimation. 8. Least Squares. 9. Method of Moments. 10. The Bayesian Philosophy. 11. General Bayesian Estimators. 12. Linear Bayesian Estimators. 13. Kalman Filters. 14. Summary of Estimators. 15. Extension for Complex Data and Parameters. Appendix: Review of Important Concepts. Glossary of Symbols and Abbreviations.
For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals - radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.