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Besides, in our network models, the nodes in the same network are nonidentical and the nodes in different networks have different state dimensions.
In both models, the nodes which transmit information have no fixed energy supplies and gain energy only via wireless energy harvesting from nature.
Considering realistic plasma and magnetic field models, the nodes (antinodes) of both the fundamental and second harmonics at L n1, L n2, and L n3 were located closer to L b2.
In the quantitative network models, the nodes represent measured levels of (phospho proteins or cellular phenotypes, and the edges represent the influence of the upstream nodes on the time derivative of their downstream effectors.
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In node system simulators with network models, the node system is often modeled by system-level description languages (SLDL), such as SystemC [35].
It models the node hardware in different abstraction levels with different degrees of detail (e.g., system level, transaction level, and register transfer level).
We use the shifted Pareto distribution to model the nodes' lifetimes in designing our protocol.
In the graphical model, the nodes correspond to probability distributions of model variables and edges to their conditional dependencies.
In this case, some key features, such as received power, are necessary to model the nodes' behavior.
To implement the proposed NWLBP model, the nodes need to record additional position information about its neighboring nodes in their lists of neighbors.
In this paper, the convergence properties of such a system are studied through algebraic graph theory, by modeling the nodes as discrete-time clocks.
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