International Journal of System Signal Control and Engineering Application
ISSN: OnlineISSN: Print 1997-5422
Abstract
In this study, I consider models of stochastic process correlation functions and, by way of numerical calculation, prove that the efficiency of optimal linear interpolation and forecasting is determined by the existing highest derivative of a stochastic process. I also set out the results of numerical calculations pertaining to efficiency assessment of interpolation and forecasting of finitely differentiable stochastic processes with correlation functions commonly used in practice for Wiener-Hopf filtering.
How to cite this article:
Vladimir Alekseevich Golovkov. Models of Stohastic Processes and Their use in Optimal Linear Inteprolation and Forecasting.
DOI: https://doi.org/10.36478/ijssceapp.2017.113.116
URL: https://www.makhillpublications.co/view-article/1997-5422/ijssceapp.2017.113.116