A Dynamic Boolean Network
نویسنده
چکیده
We propose a Dynamic Boolean Network in which a state of a Boolean network and an output label associated with the state are interacting with each other, and a transition matrix keeps changing perpetually. We extrapolate a mutation of a transition matrix as T → Q−1TQ where T is a transition matrix and Q is a matrix representation of a permutation P (where the objects permuted are states of DBN). And then we evaluate the results of a number of simulations with respect to ways to construct a P , and show that, in one of the simulations, linearity plays a significant role to cover all (or most of) possible transition matrices. We also refer to Probabilistic Boolean Network and Hidden Markov Model.
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تاریخ انتشار 2009