scholarly journals Markov model of data measurement complex for track geometry car

2020 ◽  
Vol 224 ◽  
pp. 02029
Author(s):  
V Pogorelov ◽  
E Chub

A stochastic model of a nonadjustable data measurement complex platform for track geometry cars is introduced. A state vector evaluation algorithm based on the approximation of a posteriori probability density by the system of a posteriori moments is also offered.

2021 ◽  
Vol 2131 (2) ◽  
pp. 022090
Author(s):  
E G Chub ◽  
V A Pogorelov

Abstract The described method of structure identification of the state vector of a telecommunication system stochastic model is based on a posteriori probability density approximation (APDA) by a system of a posteriori moments. An assumption of possible APDA approximation by a class of Pearson distributions resulted in a closed system of moment equations. Implementation of optimal non-linear stochastic object control techniques helped to solve the problem of structural identification. Introduction of the proposed approach into contemporary telecommunication systems will not impose additional requirements on the calculating equipment, thus making this method well-suited for a wide range of applications.


1999 ◽  
Vol 105 (2) ◽  
pp. 1365-1366
Author(s):  
Thomas J. Green ◽  
William H. Payne ◽  
Vivian E. Titus ◽  
Eric J. Van Allen

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