On General Case of Universal Hypothesis Optimal Testing for L ≥ ۲ Differently Distributed for Markov Chains

In this paper‎, ‎we study a model of hypotheses testing consisting of two simple homogeneous stationary Markov chains with a finite number of states such that having different distributions from L≥ ۲ possible transition probabilities‎. ‎The matrix of all possible pairs of asymptotical interdependence of the error probability exponents for logarithmically asymptotically optimal testing is determined‎. ‎For this aim‎, ‎we apply the method of type and large deviation techniques.

کلیدواژه ها:

Different distribution ، Error probability ، Markov chains ، Reliability ، Transition probability