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Modeling, estimation and optimal filtering in signal processing

Author: Mohamed Najim
Publisher: London ; ISTE ; Hoboken, NJ : J. Wiley & Sons, 2008.
Series: Digital signal and image processing series.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Najim, Mohamed.
Modeling, estimation and optimal filtering in signal processing.
London : ISTE ; Hoboken, NJ : J. Wiley & Sons, 2008
(DLC) 2007046085
(OCoLC)180989642
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Mohamed Najim
ISBN: 9780470393680 0470393688 9780470611104 0470611103 1848210221 9781848210226
OCLC Number: 593301449
Description: 1 online resource (xv, 392 pages) : illustrations.
Contents: 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).
Series Title: Digital signal and image processing series.
Other Titles: Modelisation, estimation et filtrage optimal en traitement du signal.
Responsibility: Mohamed Najim.
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-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 Read more...

 
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