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Exact(10)
The selection of hidden nodes can then be regarded as a subset model selection in linear regression.
These polled nodes can then transmit without any contention.
In irregular codes, variable nodes with high degree typically correct their value quickly and these nodes can then help to correct lower degree variable nodes.
With this assumption, the algorithm can run in a distributed fashion, and the computational complexity at the sampling nodes can then be reduced.
These captured nodes can then be reprogrammed and deployed within the network area, for instance, to subvert the data aggregation or the decision making process in the network [1].
Nodes can then be classified according to their appearance.
Similar(50)
Node can then compute a pairwise key with node through.
The transactive node can then decide whether to accept one or more of these offers.
Each node can then locally compute the product of the likelihoods as in (10) and obtain identical, optimal global importance weights w n ( q ).
During term T, if a node keeps in the active and the sleeping states for T1 and T0=(T−T1), respectively, the duty cycle of this node can then be expressed with (frac {T_{1}}{T_{1}+ T_{0}}).
The wireless transmission range r 0 of each node can then be calculated as the equivalent transmission power using a receiving threshold, P rx,th, also referred to as the reception sensitivity.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com