Abstract
Second-and higher-order almost cyclostationary processes are random signals with almost periodically time-varying statistics. The class includes stationary and cyclostation-ary processes as well as many real-life signals of interest. Cyclic and time-varying cumulants and polyspectra are defined for discrete-time real kth-order cyclostationary processes, and their interrelationships are explored. Smoothed polyperiodograms are proposed for cyclic polyspectral estimation and are shown to be consistent and asymptotically normal. Asymptotic covariance expressions are derived along with their computable forms. Higher than second-order cyclic cumulants and polyspectra convey time-varying phase information and are theoretically insensitive to any stationary (for nonzero cycles) as well as additive cyclostationary Gaussian noise (for all cycles).
| Original language | English (US) |
|---|---|
| Pages (from-to) | 67-84 |
| Number of pages | 18 |
| Journal | IEEE Transactions on Information Theory |
| Volume | 40 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1994 |
Bibliographical note
Funding Information:Manuscript received March 6, 1992; revised September 30, 1992. This work was supported in part by the National Science Foundation under Grant ME’ 9210230 and under ONR Grant N00014-93-1-0485. This paper was presented in part at the 25th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, Nov. 4-6, 1991.
Keywords
- Nonstationary spectral analysis
- asymptotic distribution and variance
- cyclostationary sequences
- higher order statistics
- nonparametric cyclic-polyspectrum estimation consistemcy