Digital Spectral Analysis: Parametric, Non-Parametric and Advanced Methods

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Francis Castanié
John Wiley & Sons, Feb 4, 2013 - Mathematics - 400 pages
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Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.
The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.
An entire chapter is devoted to the non-parametric methods most widely used in industry.
High resolution methods are detailed in a further four chapters: spectral analysis by stationary time series modeling, minimum variance, and subspace-based estimators.
Finally, advanced concepts are the core of the last four chapters: spectral analysis of non-stationary random signals, space time adaptive processing: irregularly sampled data processing, particle filtering and tracking of varying sinusoids.
Suitable for students, engineers working in industry, and academics at any level, this book provides a rare complete overview of the spectral analysis domain.
 

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Contents

Preface
Fundamentals
NONPARAMETRIC METHODS
Digital Signal Processing
Spectral Analysis by Parametric Modeling
SubspaceBased Estimators and Application
Minimum Variance
Exact
Introduction to Spectral Analysis of Non
Spectral Analysis of Nonuniformly Sampled
Particle Filtering and Tracking of VaQring
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