On Transient Phenomena in Branching Random Processes with Discrete Time

В данной работе рассматриваются ветвящиеся случайные процессы с дискретным временем в двух предположениях: в начальный момент времени имеется одна частица или в начальный момент времени существует большое число частиц. В переходных явлениях для таких ветвящихся случайных процессов получены оценки скорости сходимости условных законов распределений к предельному распределению. We consider branching random processes with discrete time in two assumptions: at the initial moment of time there is one particle and there are large number of particles. In transition phenomena for such branching random processes, estimates of the convergence rate of conditional distributions are obtained.

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On modeling of self-similar random processes in discrete-time

Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380) ◽

10.1109/tfsa.1998.721428 ◽

2002 ◽

Cited By ~ 6

Author(s):

Wei Zhao ◽

R.M. Rao

Keyword(s):

Discrete Time ◽

Random Processes ◽

Self Similar

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COUPLING INTERACTING PARTICLE SYSTEMS

Reviews in Mathematical Physics ◽

10.1142/s0129055x93000139 ◽

1993 ◽

Vol 05 (03) ◽

pp. 457-475 ◽

Cited By ~ 7

Author(s):

CHRISTIAN MAES

Keyword(s):

Convergence Rate ◽

Discrete Time ◽

Continuous Time ◽

Interacting Particle Systems ◽

Random Processes ◽

Particle Systems ◽

Time Process ◽

Probabilistic Cellular Automata ◽

Interacting Particle ◽

Continuous Time Process

We consider random processes (probabilistic cellular automata or interacting particle systems) defined through the interaction of an infinite number of components. We show how coupling arguments yield simple yet quite general ergodicity theorems. The relation between discrete time and continuous time versions is analyzed via similar techniques and the explicit convergence rate of discrete time approximations to the continuous time process is obtained.

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