Fundamentals of Statistical Processing, Volume I

Estimation Theory
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ISBN-13:
9780133457117
Veröffentl:
1993
Erscheinungsdatum:
26.03.1993
Seiten:
608
Autor:
Steven M. Kay
Gewicht:
1042 g
Format:
238x183x28 mm
Sprache:
Englisch
Beschreibung:
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.

A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms.
Intended for practicing engineers and scientists who design and analyze signal processing systems. This work offers a unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms.
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.

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