Prentice Hall
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Fundamentals of Statistical Processing, Volume I: Estimation Theory
ISBN-10: 0133457117
ISBN-13: 9780133457117
Publisher: Prentice Hall
Copyright: 1993
Format: Cloth; 625 pp
Published: 03/26/1993
Status: Instock
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.
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