Authors : Vladimir Alekseevich Golovkov
Abstract: The study suggests analytical expressions for algorithms of optimal linear prediction of a random process relyingon a sample of the process values and values of its derivatives at a previous instant of time. I also investigate relative efficiency of such algorithms in comparison to transversal algorithms, exemplified by a stochastic process with a finite correlation function.
Vladimir Alekseevich Golovkov , 2017. Non-Recursive Prediction of Random Processes. International Journal of Signal System Control and Engineering Application, 10: 117-120.