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Generalizations of Cyclostationary Signal Processing : Spectral Analysis and Applications.
The relative motion between the transmitter and the receiver modifies the nonstationarity properties of the transmitted signal. In particular, the almost-cyclostationarity property exhibited by almost all modulated signals adopted in communications, radar, sonar, and telemetry can be transformed int...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Wiley,
2012.
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| Colección: | Wiley - IEEE.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Generalizations of Cyclostationary Signal Processing: Spectral Analysis and Applications; Contents; About the Author; Acknowledgements; Preface; List of Abbreviations; 1 Background; 1.1 Second-Order Characterization of Stochastic Processes; 1.1.1 Time-Domain Characterization; 1.1.2 Spectral-Domain Characterization; 1.1.3 Time-Frequency Characterization; 1.1.4 Wide-Sense Stationary Processes; 1.1.5 Evolutionary Spectral Analysis; 1.1.6 Discrete-Time Processes; 1.1.7 Linear Time-Variant Transformations; 1.2 Almost-Periodic Functions; 1.2.1 Uniformly Almost-Periodic Functions.
- 1.2.2 AP Functions in the Sense of Stepanov, Weyl, and Besicovitch1.2.3 Weakly AP Functions in the Sense of Eberlein; 1.2.4 Pseudo AP Functions; 1.2.5 AP Functions in the Sense of Hartman and Ryll-Nardzewski; 1.2.6 AP Functions Defined on Groups and with Values in Banach and Hilbert Spaces; 1.2.7 AP Functions in Probability; 1.2.8 AP Sequences; 1.2.9 AP Sequences in Probability; 1.3 Almost-Cyclostationary Processes; 1.3.1 Second-Order Wide-Sense Statistical Characterization; 1.3.2 Jointly ACS Signals; 1.3.3 LAPTV Systems; 1.3.4 Products of ACS Signals.
- 1.3.5 Cyclic Statistics of Communications Signals1.3.6 Higher-Order Statistics; 1.3.7 Cyclic Statistic Estimators; 1.3.8 Discrete-Time ACS Signals; 1.3.9 Sampling of ACS Signals; 1.3.10 Multirate Processing of Discrete-Time ACS Signals; 1.3.11 Applications; 1.4 Some Properties of Cumulants; 1.4.1 Cumulants and Statistical Independence; 1.4.2 Cumulants of Complex Random Variables and Joint Complex Normality; 2 Generalized Almost-Cyclostationary Processes; 2.1 Introduction; 2.2 Characterization of GACS Stochastic Processes; 2.2.1 Strict-Sense Statistical Characterization.
- 2.2.2 Second-Order Wide-Sense Statistical Characterization2.2.3 Second-Order Spectral Characterization; 2.2.4 Higher-Order Statistics; 2.2.5 Processes with Almost-Periodic Covariance; 2.2.6 Motivations and Examples; 2.3 Linear Time-Variant Filtering of GACS Processes; 2.4 Estimation of the Cyclic Cross-Correlation Function; 2.4.1 The Cyclic Cross-Correlogram; 2.4.2 Mean-Square Consistency of the Cyclic Cross-Correlogram; 2.4.3 Asymptotic Normality of the Cyclic Cross-Correlogram; 2.5 Sampling of GACS Processes; 2.6 Discrete-Time Estimator of the Cyclic Cross-Correlation Function.
- 2.6.1 Discrete-Time Cyclic Cross-Correlogram2.6.2 Asymptotic Results as N → ∞; 2.6.3 Asymptotic Results as N → ∞ and Ts → 0; 2.6.4 Concluding Remarks; 2.7 Numerical Results; 2.7.1 Aliasing in Cycle-Frequency Domain; 2.7.2 Simulation Setup; 2.7.3 Cyclic Correlogram Analysis with Varying N; 2.7.4 Cyclic Correlogram Analysis with Varying N and Ts; 2.7.5 Discussion; 2.7.6 Conjecturing the Nonstationarity Type of the Continuous-Time Signal; 2.7.7 LTI Filtering of GACS Signals; 2.8 Summary; 3 Complements and Proofs on Generalized Almost-Cyclostationary Processes.