Properties of Stationarity and Cyclostationarity of Conditional Linear Random Processes

Abstract

A conditional linear random process (CLRP) is defined and analysed as a physically reasonable mathematical model of random signal which is generated in the form of a sum of large quantity of stochastically dependent random functions (impulses) which occur at the Poisson moments of time. The expressions of moment functions of first and second order have been presented, the conditions for CLRP to be wide sense stationary and periodically correlated have been proven. Using a characteristic function method the conditions for CLRP to be strict sense stationary and cyclostationary have been proven.