Periodicity retrieval from nonstationary signals using joint order statistics

Composite signals are nonstationary processes consisting of trend, noise and cyclic components. A cyclic component consists of periodic or almost periodic data. In this paper we present a method based on nonlinear order statistics that evaluates the fundamental period of a cyclic component. This information can be used for decomposition of composite signals.