The stepwise time dependent backward Kolmogorov equations with delayed neutrons in counting statistics II. Covariance

1983 ◽  
Vol 205 (3) ◽  
pp. 505-510
Author(s):  
F. Carloni ◽  
M. Marseguerra
Keyword(s):  
Time Dependent ◽  
Kolmogorov Equations ◽  
Delayed Neutrons ◽  
Counting Statistics

FINDING NON-STATIONARY STATE PROBABILITIES OF G-NETWORK WITH SIGNALS AND CUSTOMERS BATCH REMOVAL

2017 ◽  
Vol 31 (4) ◽  
pp. 396-412 ◽  
Author(s):  
Mikhail Matalytski
Keyword(s):  
Stationary State ◽  
Recurrence Relations ◽  
Queueing Network ◽  
Stationary Regime ◽  
Time Dependent ◽  
Successive Approximations ◽  
Method Of Successive Approximations ◽  
Kolmogorov Equations ◽  
Modified Method ◽  
Dependent State

This paper is devoted to the research of an open Markov queueing network with positive customers and signals, and positive customers batch removal. A way of finding in a non-stationary regime time-dependent state probabilities has been proposed. The Kolmogorov system of difference-differential equations for state probabilities of such network was derived. The technique of its building, based on the use of the modified method of successive approximations combined with a series method, has been proposed. It is proved that the successive approximations converge over time to the stationary state probabilities, and the sequence of approximations converges to the unique solution of the Kolmogorov equations. Any successive approximation can be represented as a convergent power series with infinite radius of convergence, the coefficients of which satisfy the recurrence relations; that is useful for estimations. Model example illustrating the finding of time-dependent state probabilities of the network has been provided.

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