Fundamentals of Statistical Processing

Estimation Theory, Volume 1

Steven Kay (Autor)

Buch | Hardcover

608 Seiten

1993
Pearson (Verlag)
978-0-13-345711-7 (ISBN)

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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.

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.

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.

Erscheint lt. Verlag	8.5.1993
Sprache	englisch
Maße	180 x 238 mm
Gewicht	1040 g
Themenwelt	Informatik ► Grafik / Design ► Digitale Bildverarbeitung
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Technik ► Nachrichtentechnik
ISBN-10	0-13-345711-7 / 0133457117
ISBN-13	978-0-13-345711-7 / 9780133457117
Zustand	Neuware