Figure 2 Limit probability distribution of states versus.
The corresponding transition matrix becomes (9). Figure 2 shows the limit probability distribution of the states versus for the described Markov chain.
The fact that all moments exist is not enough to guarantee that there exists a limit probability measure having these moments.
In the continuous time limit probability distortions may be replaced by measure distortions (Madan et al. 2016) of arrival rate functions to construct upper and lower prices and their associated risk exposures.
A 95% connection limit probability was used, where gaps were treated as missing with no connection limit step priors.
Thanks to the tree structure of state diagram, we are able to compute the limiting probabilities in closed form via (17).
On the opposite, in a scenario with an ideal MAC protocol, this limiting probability does not depend on [8].
Finally, note that the limiting probability (17) equals to zero for any unbalanced configuration with at least one cluster with one sensor.
where π i is the limiting probability that the system is in state i and S is the state space of the Markov chain.
The solutions to some fundamental problems in non-linear systems such as bifurcations, steady state solutions, limiting probability distribution of steady state solutions, domains of attraction and basin boundaries are obtained.
