ISBN: 9781905209743 - discrete stochastic processes and optimal filtering (24 risultati)

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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 287 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Condizione: 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 navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. Series: Digital Signal & Image Processing. Num Pages: 288 pages, Illustrations. BIC Classification: PBWL. Category: (P) Professional & Vocational. Dimension: 238 x 164 x 21. Weight in Grams: 586. . 2007. Hardcover. . . . .…

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Hardback. Condizione: 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 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.…

Hardcover. Condizione: Brand New. illustrated edition. 288 pages. 9.25x6.25x0.75 inches. In Stock.

Condizione: 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.

Buch. Condizione: Neu. Neuware - 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.…

Condizione: 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 navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. Series: Digital Signal & Image Processing. Num Pages: 288 pages, Illustrations. BIC Classification: PBWL. Category: (P) Professional & Vocational. Dimension: 238 x 164 x 21. Weight in Grams: 586. . 2007. Hardcover. . . . . Books ship from the US and Ireland.…

Buch. Condizione: Neu. Discrete Stochastic Processes and Optimal Filtering | Jean-Claude Bertein (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2007 | Wiley | EAN 9781905209743 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…

Hardback. Condizione: 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 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.…