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Fundamentals of Statistical Processing, Volume 1: Estimation Theory (Paperback )  | Released: 2009

By: Steven M Kay (Author)   Publisher: Pearson Education
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This book is written on parameter estimation range from highly theoretical to more practical applied statistics. This book strikes a balance between these 2 extremes. Audience is community involved in design and implementation of signal processing algoriTable of Contents: 1. Introduction. 2. Minimum Variance Unbiased Estimation. 3. Cramer-Rao Lower Bound.... Read More

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Author:

Steven M Kay

Publisher Name:

Pearson Education

Language:

English

Binding:

(Paperback )

About The Book
This book is written on parameter estimation range from highly theoretical to more practical applied statistics. This book strikes a balance between these 2 extremes. Audience is community involved in design and implementation of signal processing algoriTable 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