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Lessons in estimation theory for signal processing, communications, and control

Author: Jerry M Mendel
Publisher: Englewood Cliffs, N.J. : Prentice Hall PTR, ©1995.
Series: Prentice-Hall signal processing series.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:

An introduction to the field of estimation theory. It is in a lesson format and so can be used for self-study or in a one semester course. The computation that is essential in order to use the  Read more...

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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Jerry M Mendel
ISBN: 9780132442206 0132442205 0131209817 9780131209817
OCLC Number: 297574969
Description: 1 online resource (xix, 561 pages) : illustrations.
Contents: 1. Introduction, Coverage, Philosophy, and Computation. 2. The Linear Model. 3. Least-Squares Estimation: Batch Processing. 4. Least-Squares Estimation: Singular-Value Decomposition. 5. Least-Squares Estimation: Recursive Processing. 6. Small Sample Properties of Estimators. 7. Large Sample Properties of Estimators. 8. Properties of Least-Squares Estimators. 9. Best Linear Unbiased Estimation. 10. Likelihood. 11. Maximum-Likelihood Estimation. 12. Multivariate Gaussian Random Variables. 13. Mean-Squared Estimation of Random Parameters. 14. Maximum A Posteriori Estimation of Random Parameters. 15. Elements of Discrete-Time Gauss-Markov Random Sequences. 16. State Estimation: Prediction. 17. State Estimation: Filtering (The Kalman Filter). 18. State Estimation: Filtering Examples. 19. State Estimation: Steady-State Kalman Filter and Its Relationships to a Digital Wiener Filter. 20. State Estimation: Smoothing. 21. State Estimation: Smoothing (General Results). 22. State Estimation for the Not-So-Basic State-Variable Model. 23. Linearization and Discretization of Nonlinear Systems. 24. Iterated Least Squares and Extended Kalman Filtering. 25. Maximum-Likelihood State and Parameter Estimation. 26. Kalman-Bucy Filtering. A. Sufficient Statistics and Statistical Estimation of Parameters. B. Introduction to Higher-Order Statistics. C. Estimation and Applications of Higher-Order Statistics. D. Introduction to State-Variable Models and Methods. Appendix A: Glossary of Major Results. Appendix B: Estimation of Algorithm M-Files. References. Index.
Series Title: Prentice-Hall signal processing series.
Responsibility: Jerry M. Mendel.

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