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Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. Series: ISTE. Num Pages: 320 pages, Illustrations. BIC Classification: PBWL; TJK; UYS. Category: (P) Professional & Vocational. Dimension: 238 x 156 x 22. Weight in Grams: 580. . 2010. 2nd Edition. Hardcover. . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9781848211810
Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using MATLAB.
À propos de l?auteur:
Jean-Claude Bertein has a Master's and PhD degree from the University of Paris VI. He was formerly a research engineer at Alcatel and today is Professor in the Department of Mathematics and Physics at the Graduate School of Electrical and Electronic Engineering (ESIEE) Paris.
Roger Ceschi is an ENSEA engineer and holds a Master's and PhD degree from the University of Paris XI. He was formerly Director of the ENSEA and today he is Director General of the ESIEE Amiens. He is also the author of a theorem on analytic signals and is Visiting Professor at the BIPT and BIT Universities in China.
Titre : Discrete Stochastic Processes and Optimal ...
Éditeur : ISTE Ltd and John Wiley & Sons Inc
Date d'édition : 2010
Reliure : Couverture rigide
Etat : New
Edition : 2ème Édition
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Hardcover. Etat : new. Hardcover. Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using MATLAB. Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781848211810
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Gebunden. Etat : New. Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigati. N° de réf. du vendeur 556580852
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Hardcover. Etat : new. Hardcover. Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using MATLAB. Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781848211810
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