61953

Автор(ы): 

Зверкина Г. А. (ИПУ РАН, Лаборатория 27)

Автор(ов): 

1

Параметры публикации

Тип публикации: 

Доклад

Название: 

Ergodicity and Polynomial Convergence Rate of Generalized Markov Modulated Poisson Processes

Электронная публикация: 

Да

ISBN/ISSN: 

ISBN 978-3-030-66241-7

DOI: 

https://doi.org/10.1007/978-3-030-66242-4 _ 29

Наименование конференции: 

  • 23rd International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2020, Moscow)

Наименование источника: 

  • Proceedings of the 23rd International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2020, Moscow)

Обозначение и номер тома: 

Vol.1337

Город: 

  • Cham

Издательство: 

  • Springer

Год издания: 

2021

Страницы: 

367-381
Аннотация
Generalization of the Lorden’s inequality is an excellent toolfor obtaining strong upper bounds for the convergence rate for variouscomplicated stochastic models. This paper demonstrates a method forobtaining such bounds for some generalization of the Markov modulatedPoisson process (MMPP). The proposed method can be applied in thereliability and queuing theory

Библиографическая ссылка: 

Зверкина Г.А. Ergodicity and Polynomial Convergence Rate of Generalized Markov Modulated Poisson Processes / Proceedings of the 23rd International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2020, Moscow). Cham: Springer, 2021. Vol.1337. С. 367-381.