科研之友
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摘要
We introduce a wavelet characterization of continuous-time periodically correlated processes based on a linear combination of infinite-dimensional stationary processes. The finite version of this linear combination converges to the main process. The first-order and second-order estimators based on the wavelets are presented. Under a simple and easy algorithm, the periodically correlated process is simulated for a given autocovariance function. The proposed algorithm has two main advantages: first, it is fast, and second, it is distribution free. We indicate through four examples that the simulated data are periodically correlated with the desired period.
- 出版日期2016-11
