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1st Edition - October 24, 2019
Author: Antonio Napolitano
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… Read more
Immediately download your ebook while waiting for your print delivery. No promo code is needed.
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.
Researchers and graduate students in electronic engineering, Stochastic Processes, Harmonic analysis, and Applied Mathematics
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
AN