Rate of convergence in fuzzy non homogeneous Markov systems

Abstract

ABSTRACTCertain aspects of convergence rate in a non-homogeneous Markov system (NHMS) using fuzzy set theory and fuzzy reasoning are presented in this paper. More specifically, a fuzzy non-homogeneous Markov system is considered where fuzzy inference systems are used to estimate the transition probabilities, the input and loss probabilities and the population structure of the system. It is proved that under some conditions easily met in practice, the rate of convergence of the sequence of the relative population structures in such a system is geometric, i.e. it converges to its limit geometrically fast.