Modeling, Estimation and Optimal Filtration in Signal Processing
Ene 2010 · ISTE Aklat 25 · Ibinebenta ng John Wiley & Sons
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400
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Tungkol sa ebook na ito
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.
Tungkol sa may-akda
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.
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