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Fundamentals of Statistical Processing, Volume I
Estimation Theory
Buch von Steven M. Kay
Sprache: Englisch

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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.

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.

Inhaltsverzeichnis

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.
Details
Erscheinungsjahr: 1993
Genre: Technik allg.
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 608
ISBN-13: 9780133457117
ISBN-10: 0133457117
Sprache: Englisch
Einband: Gebunden
Autor: Kay, Steven M.
Hersteller: Prentice Hall
Pearson Higher Education
Maße: 183 x 238 x 28 mm
Von/Mit: Steven M. Kay
Erscheinungsdatum: 26.03.1993
Gewicht: 1,042 kg
preigu-id: 106832348
Inhaltsverzeichnis

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.
Details
Erscheinungsjahr: 1993
Genre: Technik allg.
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 608
ISBN-13: 9780133457117
ISBN-10: 0133457117
Sprache: Englisch
Einband: Gebunden
Autor: Kay, Steven M.
Hersteller: Prentice Hall
Pearson Higher Education
Maße: 183 x 238 x 28 mm
Von/Mit: Steven M. Kay
Erscheinungsdatum: 26.03.1993
Gewicht: 1,042 kg
preigu-id: 106832348
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