Using the censoring technique, we systematically constructed and devoloped two types of RG-factorizations: 1) UL-type RG-factorization, and 2) LU-type RG-factorization. These RG-factorizations are very useful in the study of, such as, QBD processes, Markov processes, Markov renewal processes, Markov reward processes, Markov decision processes, stochastic game theory and their practical applications. Our recent works indicate that the two types of RG-factorizations play a different important role in the study of stochastic models, for example, the UL-type RG-factorization is a key to deal with stationary solution to performance measures  while LU-type RG-factorization can be used to analyze transient solution to performance measures. We have an optimistic prediction that the RG-factorizations are very useful for sharpening many important research on stochastic processes, stochastic models, computer networks, manufacturing systems, transportation systems and biological sciences etc.

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Using the censoring technique, we systematically devoloped two types of RG-factorizations. These RG-factorizations are very useful in the study of, such as, QBD processes, Markov processes, Markov renewal processes, Markov reward processes, Markov decision processes, stochastic game theory and their practical applications. Our recent works indicate that the two types of RG-factorizations play a different important role in the study of stochastic models.
创建时间:2021-09-29 07:00