Bratus O.V.

Construction of Multidimensional Models Based on Kalman Filter and Analysis of Estimation Algorithms of its Parameters

In this paper, we construct the algorithms for estimating mathematical expectation of accelerating the values change of data sample. Simulation modeling is based on these algorithms for the random process. Based on its results, we analyze and choose best algorithms. We show that estimation of mathematical expectation of accelerating values change of data samples for constructed selective sequences of discrepancies does not show better results compared with its estimation based on a full sequence of discrepancies. Adaptive Kalman filter is constructed.