Modeling, Estimation and Optimal Filtration in Signal Processing - Hardcover

Najim, Mohamed

 
9781848210226: Modeling, Estimation and Optimal Filtration in Signal Processing

Synopsis

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.

"synopsis" may belong to another edition of this title.

About the Author

Mohamed Najim is Professor in signal processing at the ENSEIRB and Université Bordeaux I (France), where he leads the Signal and Image Processing group.
An IEEE Fellow, he has worked in adaptive control and in the field of 1D and n-D identification in signal and image processing.

From the Back Cover

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.

From the Inside Flap

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.

"About this title" may belong to another edition of this title.