The machine capacity process is assumed to be a finite state Markov chain.
As the underlying model of probabilistic Boolean networks is a finite Markov chain, we define the network sensitivity based on the steady-state distributions of probabilistic Boolean networks and call it long-run sensitivity.
In a random walk, the node-visiting sequence of the walker is a finite state Markov chain, which is only related to the currently visited node rather than the previous sequence of nodes.
It is equivalent to the existence of a finite chain J1 ⊂ J2 ⊂ … ⊂ J
The statistics from the trace-based data indicates that it is a finite, irreducible and ergodic Markov chain.
Also, if P i i T > 0 and P T contains non-negative entries then (P T ) i i (t ) > 0 for all t ≥ 0. So, it is a finite, aperiodic and irreducible Markov chain.
A PAA is a tuple (Q, q0, T, E, (π q ) q ∈ Q, N, n0, (θ q ) q ∈ Q ), where (1) (Q, q0, T) is a Markov chain: Q is a finite set of states, q0 ∈ Q is called start state (it may be alternatively replaced by a probability distribution over all states), (T p, q)) p, q ∈ Q is a stochastic transition matrix.
The NHS budget is a finite resource.
"So there's a finite number".
