Sentence examples for this set of network from inspiring English sources

In order to impose this set of network loads, each ST station generates a tuple of VO, VI and BK packets at a predefined data rate.

The basic topological descriptors (global clustering coefficient, edge density, and average distance) showed no sufficient classification ability for this set of network data, when applying ANOVA.

However, existing methods usually select a single network from them for classification and the discriminative power of this set of networks has not been fully exploited.

In this set of networks data moves in only one direction forward from the input layer to the hidden layer and then to the output.

We could demonstrate that different groups of topological network descriptors perform differently on this set of networks.

Also, our results reveal that entropy-based descriptors show the highest classification ability for this set of networks.

The generation of this set of networks relied on both manual curation of published literature and a data-driven reverse causal reasoning (RCR) methodology to augment the causal biological framework underlying the network architecture.

The other group, entropy-based descriptors (EBD), is formed by merging groups 3 and 4. Based on previous observations, we expect EBD to perform better on classifying this set of networks.

This set of model networks also generated network-wide bursts within 200 300 ms following brief focal glutamatergic stimulation of five or more constituent neurons in agreement with focal glutamate un-caging experiments in neonatal mouse slices, which showed that simultaneous stimulation of 4 9 preBötC neurons can trigger inspiratory bursts with similar latency (Kam et al., 2013b).

This set of 50 network models is also available in the CBN database as version 1.1 of the network models.

An ad hoc wireless network is represented by an undirected graph, G = (V, E), where V is the set of network nodes and E is the set of network bidirectional links.