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Modeling, Estimation and Optimal Filtration in Signal Processing

Modeling, Estimation and Optimal Filtration in Signal Processing

Mohamed Najim

ISBN: 978-0-470-39368-0

Jan 2010, Wiley-ISTE

400 pages



The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing.
Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed.
Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented.
Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and their variants.
Chapter 1. Introduction to Parametric Models.

Chapter 2. Least-Squares Estimation of Linear Model Parameters.

Chapter 3. Matched Filters and Wiener Filters.

Chapter 4. Adaptive Filters.

Chapter 5. Kalman Filters.

Chapter 6. Kalman Filtering for Speech Enhancement.

Chapter 7.  Instrumental Variable Techniques.

Chapter 8.  H Infinity Techniques: An Alternative to Kalman filters?

Chapter 9.  Introduction to Particle Filtering.

"This book provides the reader for the first time with a comprehensive collection of the significant results obtained to date in the field of parametric signal modeling and presents a number of new approaches." (Mathematical Reviews, 2010)