Modeling, Estimation and Optimal Filtration in Signal Processing
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A01=Mohamed Najim
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Author_Mohamed Najim
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Category=UYS
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estimation
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least squares
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linear
methods
models
optimal
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rls
sinusoidal
traditional methods
Product details
- ISBN 9781848210226
- Weight: 748g
- Dimensions: 163 x 241mm
- Publication Date: 06 Jun 2008
- Publisher: ISTE Ltd and John Wiley & Sons Inc
- Publication City/Country: GB
- Product Form: Hardback
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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.
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.
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.
An IEEE Fellow, he has worked in adaptive control and in the field of 1D and n-D identification in signal and image processing.
