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Cyclostationary Processes and Time Series
Theory, Applications, and Generalizations

Helps readers learn about cyclostationarity methods and how to apply signal processing algorithms to optimize performance

Antonio Napolitano (Author)

9780081027080, Elsevier Science

Paperback / softback, published 28 October 2019

626 pages
23.4 x 19 x 3.8 cm, 1.43 kg

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.

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

Subject Areas: Signal processing [UYS]

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