on the detection and estimation of the simple harmonizable processes

simple harmonizable processes (shp) introduced by soltani and parvardeh (2006) are a large class of nonstationary processes which includes stationary and periodically correlated (pc) processes. detection and estimation of shp structure are important problems when dealing with nonstationary data. in this paper, we study the spectral properties of simple processes and propose a method to detect and estimate shp structure. as an example, we discuss the detection, estimation and prediction of periodically correlated processes. the performance of this method is investigated through extensive monte carlo simulations. this method is compatible with other method.