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Modeling, estimation and optimal filtering in signal processing /

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 a...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Najim, Mohamed
Formato: Electrónico eBook
Idioma:Inglés
Francés
Publicado: London ; ISTE ; Hoboken, NJ : J. Wiley & Sons, 2008.
Colección:Digital signal and image processing series.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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240 1 0 |a Modelisation, estimation et filtrage optimal en traitement du signal.  |l English 
245 1 0 |a Modeling, estimation and optimal filtering in signal processing /  |c Mohamed Najim. 
260 |a London ;  |a ISTE ;  |a Hoboken, NJ :  |b J. Wiley & Sons,  |c 2008. 
300 |a 1 online resource (xv, 392 pages) :  |b illustrations 
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338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Digital signal and image processing series 
504 |a Includes bibliographical references and index. 
505 0 |a Parametric models -- Least squares estimation of parameters of linear models -- Matched and Wiener filters -- Adaptive filtering -- Kalman filtering -- Application of the Kalman filter to signal enhancement -- Estimation using the instrumental variable technique -- H [infinity symbol] estimation : an alternative to Kalman filtering? -- Introduction to particle filtering -- Karhunen Loeve transform -- Subspace decomposition for spectral analysis -- Subspace decomposition applied to speech enhancement -- From AR parameters to line spectrum pair -- Influence of an additive white noise on the estimation of AR parameters -- The Schur-Cohn algorithm -- The gradient method -- An alternative way of understanding Kalman filtering -- Calculation of the Kalman gain using the Mehra approach -- Calculation of the Kalman gain (the Carew and Belanger method) -- The unscented Kalman filter (UKF). 
588 0 |a Print version record. 
520 |a 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 the. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Electric filters, Digital. 
650 0 |a Signal processing  |x Digital techniques. 
650 6 |a Filtres numériques. 
650 6 |a Traitement du signal  |x Techniques numériques. 
650 7 |a COMPUTERS  |x Information Theory.  |2 bisacsh 
650 7 |a TECHNOLOGY & ENGINEERING  |x Signals & Signal Processing.  |2 bisacsh 
650 7 |a Electric filters, Digital  |2 fast 
650 7 |a Signal processing  |x Digital techniques  |2 fast 
776 0 8 |i Print version:  |a Najim, Mohamed.  |s Modelisation, estimation et filtrage optimal en traitement du signal. English.  |t Modeling, estimation and optimal filtering in signal processing.  |d London : ISTE ; Hoboken, NJ : J. Wiley & Sons, 2008  |z 9781848210226  |w (DLC) 2007046085  |w (OCoLC)180989642 
830 0 |a Digital signal and image processing series. 
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