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Secure Connected Objects

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Banach, Fréchet, Hilbert and Neumann Spaces

Analysis for PDEs Set – Volume 1

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Semi-Markov Migration Models for Credit Risk

Stochastic Models for Insurance Set – Volume 1

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Human Exposure to Electromagnetic Fields

From Extremely Low Frequency (ELF) to Radio Frequency

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Enterprise Interoperability


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Data Treatment in Environmental Sciences

Multivaried Approach

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From Pinch Methodology to Pinch-Exergy Integration of Flexible Systems

Thermodynamics – Energy, Environment, Economy Set

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Exterior Algebras

Elementary Tribute to Grassmann's Ideas

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Nonlinear Theory of Elastic Plates

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Cognitive Approach to Natural Language Processing

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Digital Spectral Analysis

Parametric, Non-parametric and Advanced Methods

Edited by Francis Castanié, TeSA, Toulouse, France

ISBN: 9781848212770

Publication Date: June 2011   Hardback   400 pp.

147.00 USD

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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.


Part 1. Tools and Spectral Analysis
1. Fundamentals, Francis Castanié.
2. Digital Signal Processing, Éric Le Carpentier.
3. Introduction to Estimation Theory with Application in Spectral Analysis, Olivier Besson and André Ferrari.
4. Time-Series Models, Francis Castanié.
Part 2. Non-Parametric Methods
5. Non-Parametric Methods, Éric Le Carpentier.
Part 3. Parametric Methods
6. Spectral Analysis by Parametric Modeling,
Corinne Mailhes and Francis Castanié.
7. Minimum Variance, Nadine Martin.
8. Subspace-Based Estimators and Application to Partially Known Signal Subspaces, Sylvie Marcos and Rémy Boyer.
Part 4. Advanced Concepts
9. Multidimensional Harmonic Retrieval: Exact, Asymptotic, and Modified Cramér-Rao Bounds, Rémy Boyer.
10. Introduction to Spectral Analysis of Non-Stationary Random Signals, Corinne Mailhes and Francis Castanié.
11. Spectral Analysis of Non-uniformly Sampled Signals, Arnaud Rivoira and Gilles Fleury.
12. Space–Time Adaptive Processing, Laurent Savy and François Le Chevalier.
13. Particle Filtering and Tracking of Varying Sinusoids, David Bonacci.

About the Authors

Francis Castanié is the Director of the Research Laboratory Telecommunications for Space and Aeronautics (TeSA) in France.


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