Steven Kay
Pearson Education
1e druk, 1993
9780133457117
Fundamentals of Statistical Processing, Volume I
Estimation Theory
Specificaties
Gebonden, 608 blz.
|
Engels
Pearson Education |
1e druk, 1993
ISBN13: 9780133457117
Rubricering
Juridisch
:
Verwachte levertijd ongeveer 8 werkdagen
Samenvatting
A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms.
KEY TOPICS:
Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems.
MARKETS: 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.
Specificaties
ISBN13:9780133457117
Trefwoorden:statistiek
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:608
Uitgever:Pearson Education
Druk:1
Verschijningsdatum:1-5-1993
Hoofdrubriek:Wetenschap en techniek
Inhoudsopgave
 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.
 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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