Description

Book Synopsis
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.

Table of Contents


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.

Fundamentals of Statistical Processing

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A Hardback by Steven Kay

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    View other formats and editions of Fundamentals of Statistical Processing by Steven Kay

    Publisher: Pearson Education (US)
    Publication Date: 08/05/1993
    ISBN13: 9780133457117, 978-0133457117
    ISBN10: 0133457117
    Also in:
    Mathematics Applied mathematics

    Description

    Book Synopsis
    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.

    Table of Contents


    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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