Cyclostationary Processes and Time Series
Theory, Applications, and Generalizations
Published on 28. October 2019
Book
Paperback/Softback
626 pages
978-0-08-102708-0 (ISBN)
Description
Many processes in nature arise from the interaction of periodic phenomena with random phenomena. The results are processes that are not periodic, but whose statistical functions are periodic functions of time. These processes are called cyclostationary and are an appropriate mathematical model for signals encountered in many fields including communications, radar, sonar, telemetry, acoustics, mechanics, econometrics, astronomy, and biology.
Cyclostationary Processes and Time Series: Theory, Applications, and Generalizations addresses these issues and includes the following key features.
Cyclostationary Processes and Time Series: Theory, Applications, and Generalizations addresses these issues and includes the following key features.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Product notice
Paperback (trade)
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 32 mm
Weight
1065 gr
ISBN-13
978-0-08-102708-0 (9780081027080)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Antonio Napolitano
Cyclostationary Processes and Time Series
Theory, Applications, and Generalizations
E-Book
10/2019
Academic Press
€131.00
Available for download
Person
Antonio Napolitano is Full Professor of Telecommunications at the University of Napoli Parthenope (Italy). In 1995 he received the Best Paper of the Year Award from the European Association for Signal Processing (EURASIP) for a paper on higher-order cyclostationarity. In 2007 was recipient of the EURASIP Best Paper Award for a paper on the functional approach in signal analysis. In 2008 he received from Elsevier the Most Cited Paper Award for a review article on cyclostationarity.
In 2016 he became an IEEE Fellow. He has been Associate Editor of the IEEE Transactions on Signal Processing and is on the Editorial Board of Signal Processing (Elsevier) and Digital Signal Processing (Elsevier). He has been in the Signal Processing Theory and Methods Technical Committees (SPM-TC) and is now in the Sensor Array and Multichannel Technical Committee (SAM-TC) of the IEEE Signal Processing Society.
In 2016 he became an IEEE Fellow. He has been Associate Editor of the IEEE Transactions on Signal Processing and is on the Editorial Board of Signal Processing (Elsevier) and Digital Signal Processing (Elsevier). He has been in the Signal Processing Theory and Methods Technical Committees (SPM-TC) and is now in the Sensor Array and Multichannel Technical Committee (SAM-TC) of the IEEE Signal Processing Society.
Content
PART I CYCLOSTATIONARITY
1. Characterization of Stochastic Processes
2. Characterization of Time-Series
3 Almost-Cyclostationary Signal Processing
4. Higher-Order Cyclostationarity
5. Ergodic Properties and Measurement of Characteristics
6. Quadratic Time-Frequency Distributions
7. Manufactured Signals
8. Detection and Cycle Frequency Estimation
9. Communications Systems
10. Selected Topics and Applications
PART II GENERALIZATIONS
11. Limits of the Almost-Cyclostationary Model
12. Generalized Almost-Cyclostationary Signals
13. Spectrally Correlated Signals
14. Oscillatory Almost-Cyclostationary Signals
15. The Big Picture
PART III APPENDICES
A. Nonstationary Signal Analysis
B. Almost-Periodic Functions
C. Sampling and Replication
D. Hilbert Transform, Analytic Signal, and Complex Envelope
E. Complex Random Vectors, Quadratic Forms, and Chi Squared Distribution
F. Bibliographic Notes
1. Characterization of Stochastic Processes
2. Characterization of Time-Series
3 Almost-Cyclostationary Signal Processing
4. Higher-Order Cyclostationarity
5. Ergodic Properties and Measurement of Characteristics
6. Quadratic Time-Frequency Distributions
7. Manufactured Signals
8. Detection and Cycle Frequency Estimation
9. Communications Systems
10. Selected Topics and Applications
PART II GENERALIZATIONS
11. Limits of the Almost-Cyclostationary Model
12. Generalized Almost-Cyclostationary Signals
13. Spectrally Correlated Signals
14. Oscillatory Almost-Cyclostationary Signals
15. The Big Picture
PART III APPENDICES
A. Nonstationary Signal Analysis
B. Almost-Periodic Functions
C. Sampling and Replication
D. Hilbert Transform, Analytic Signal, and Complex Envelope
E. Complex Random Vectors, Quadratic Forms, and Chi Squared Distribution
F. Bibliographic Notes