Abstract
A method is proposed for determining the dispersion and correlation matrices for a random process that can be represented as a system of differential equations. The method provides a significant reduction of computational operations and is free of the systematic error that accompanies numerical integration. As an example we present finite expressions for the probability characteristics of observed variables.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Literature cited
H. Trees, Detection, Estimation, and Modulation, Wiley, New York (1968).
F. R. Gantmakher, Matrix Theory [in Russian], Moscow (1967).
P. D. Krut'ko, “Observation of dynamical systems as a control process,” Izv. Vyssh. Uchebn. Zaved., Radiofiz.,14, No. 7, 978–981 (1971).
V. S. Pugachev and I. N. Sinitsyn, Stochastic Differential Systems, [in Russian], Moscow (1985).
Author information
Authors and Affiliations
Additional information
Translated fromVychislitel'naya i Prikladnaya Matematika, No. 69, pp. 135–141, 1989.
Rights and permissions
About this article
Cite this article
Mikhalochkin, N.A., Geletukha, V.V. Procedure for determining the dispersion and correlation matrices for a multidimensional random process. J Math Sci 67, 3143–3148 (1993). https://doi.org/10.1007/BF01098156
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF01098156