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Spectral analysis parametric and non-parametric digital methods /

In Signal Processing, the concepts of frequency, which are usually referred to as "spectral" concepts, are omnipresent. The transition from analogue methods to the use of digital tools in spectral analysis was first achieved by simple adaptation of the classical analogue tools that had lon...

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Bibliographic Details
Group Author: Castanié, Francis
Published:
Literature type: Electronic eBook
Language: English
French
Series: Digital signal and image processing series
Subjects:
Signal processing > Digital techniques
Spectrum analysis > Statistical methods
Signal processing
COMPUTERS > Information Theory
TECHNOLOGY & ENGINEERING > Signals & Signal Processing
Electronic books
Online Access: http://onlinelibrary.wiley.com/book/10.1002/9780470612194
Summary: In Signal Processing, the concepts of frequency, which are usually referred to as "spectral" concepts, are omnipresent. The transition from analogue methods to the use of digital tools in spectral analysis was first achieved by simple adaptation of the classical analogue tools that had long been used previously. However, beyond the simple quest of methods with better frequency resolution, it has been possible to develop specific digital tools based on parametric modeling. This book deals with these parametric methods, first discussing those based on time series models, Capon's method and its
Carrier Form: 1 online resource (262 pages) : illustrations.
Bibliography: Includes bibliographical references and index.
ISBN: 9781847045553 (electronic bk.)
1847045553 (electronic bk.)
1847044557 (electronic bk.)
9781847044556 (electronic bk.)
9780470394441
0470394447
9780470612194
0470612193
Index Number: TK5102
CLC: TN911.72
Contents: Preliminaries; Contents; Preface; Chapter 1 Fundamentals; Chapter 2 Digital Signal Processing; Chapter 3 Estimation in Spectral Analysis; Chapter 4 Time Series Models; Chapter 5 Non Parametric Methods; Chapter 6 Spectral Analysis by Stationary Time Series Modeling; Chapter 7 Minimum Variance; Chapter 8 Subspace based Estimators; Chapter 9 Introduction to Spectral Analysis of Non-Stationary Random Signals; List of Authors; Index.

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