Statistical Signal Processing, 1st edition

  • Louis Scharf

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KEY BENEFITS: This book embraces the many mathematical procedures that engineers and statisticians use to draw inference from imperfect or incomplete measurements. KEY TOPICS: This book presents the fundamental ideas in statistical signal processing along four distinct lines: mathematical and statistical preliminaries; decision theory; estimation theory; and time series analysis.

Table of contents

 1. Introduction.

 2. Rudiments of Linear Algebra and Multivariate Normal Theory.

 3. Sufficiency and MVUB Estimators.

 4. Neyman-Pearson Detectors.

 5. Bayes Detectors.

 6. Maximum Likelihood Estimators.

 7. Bayes Estimators.

 8. Minimum Mean-Squared Error Estimators.

 9. Least Squares.

10. Linear Prediction.

11. Modal Analysis.

Published by Pearson (July 1st 1991) - Copyright © 1991