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We first propose a theoretical network model to generate a system with the theoretically maximal ACSD.
The other is using computer modeling method to systematically enumerate the theoretical network structures.
A theoretical network model reproducing some significant features of the viscoelastic behavior of unentangled polymer melts reinforced with well dispersed non-agglomerated nanoparticles is presented.
Moreover, this approach allows for the computation of graph theoretical network metrics to quantify the topological architecture of the brain network detected.
Theoretical network capacity and the state-of-the-art protocols for WMNs are explored with an objective to point out a number of open research issues.
The control problem here is evaluated across three different theoretical network types.
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Results demonstrating the efficacy of the learned control policies across three different types of theoretical networks are included in "Results".
The focuses of both empirical and theoretical network-theory approaches to gene regulatory networks have been studies of the degree distribution [7], [8] and network motifs [27] [30].
For some reflex responses the connectivity has been discovered by direct observation, and some theoretical networks have been proposed to explain other simple neural responses, e.g., [1] [5].
Although these theoretical networks are unlikely to be found in empirical data we do capitalize on their mathematical forms because they can provide a good feel about possible changes in the one or the other measure.
By demonstrating that the density of the binary cortical graph (i.e. present vs. absent) is much higher than previous estimates, we provide important constraints on the classes of theoretical networks that are relevant to modeling interareal connectivity.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com