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USING A PRIORI INFORMATION FOR CORRECTION OF THE EVENTS STREAM MODEL IN COMPLEX SYSTEM

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The problem of Poisson distribution parameter estimation by results of theoretical researches and limited field tests is considered. In various problems, the Poisson distribution parameter characterizes average number of casual events occur in a set time interval, or average number of points falling into a given space area. The parameter value significantly affects the cost of the developed system and the possibility of its use for a specified purpose. While it is not possible to obtain a sufficient information for evaluation of this parameter during the tests of the system prototypes, invoking an information on the flow of system events accumulated prior to the tests is necessary. A solution to the problem of estimation of the Poisson distribution parameter based on joint processing of a priori information and limited experimental data is presented. 

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