
Cyclostationary Processes and Time Series
Theory, Applications, and Generalizations
- 626 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Cyclostationary Processes and Time Series
Theory, Applications, and Generalizations
About this book
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.- Presents the foundations and developments of the second- and higher-order theory of cyclostationary signals- Performs signal analysis using both the classical stochastic process approach and the functional approach for time series- Provides applications in signal detection and estimation, filtering, parameter estimation, source location, modulation format classification, and biological signal characterization- Includes algorithms for cyclic spectral analysis along with Matlab/Octave code- Provides generalizations of the classical cyclostationary model in order to account for relative motion between transmitter and receiver and describe irregular statistical cyclicity in the data
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Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- About the Author
- Preface
- Acknowledgment
- List of Abbreviations
- Notation
- Part 1: 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: design and analysis
- 10: Selected topics and applications
- Part 2: Generalizations
- 11: Limits of the ACS model
- 12: Generalized almost-cyclostationary signals
- 13: Spectrally correlated signals
- 14: Oscillatory almost-cyclostationary signals
- 15: The big picture
- Part 3: 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
- Bibliography
- Index