Median-based cyclic polyspectrum estimation

In this paper, median-based estimation methods for the cyclic polyspectrum are proposed. The algorithms do not require a priori knowledge of the beta submanifolds, that is, they do not require the knowledge of all of the lowe r order cycle frequencies of the time-series available for the estimation o f the cyclic polyspectrum. Therefore, such methods are particularly useful when the cyclostationarity of the signals under consideration is not comple tely known. The proposed estimators converge to the theoretical values of t he cyclic polyspectrum when the collect time approaches infinity and the sp ectral resolution becomes infinitesimal. Furthermore, their accuracy is ver y nearly the same as that of the usual time- and frequency-smoothed cyclic periodogram methods that use a priori knowledge of lower-order cycle freque ncies to avoid the beta submanifolds.