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Also, except for the Sections 5.3.1 and 5.4, for the consensus weight matrix we use the metropolis weights (Eq. (2)).
When Top node Average consensus weight is not zero, we will continue our average consensus algorithm otherwise we should stop.
The most frequent food insecurity rank and thus corresponding consensus weight assigned by the agro-pastoral and pastoral community FGDs to each of the 27 CCS was noted.
For every time, we will consider the top node from the segment tree and as initially we have highest max weight edges based average consensus weight in the top node.
Table 2 Table representation binary consensus edge priority Binary protocol ID Protocol priority or consensus weight 1 5 2, 3 4 4 3 5, 6 2 7 1 8 0. Let us describe the situation in Fig. 4. First node B and C run updating protocol.
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Fig. 2 Time evolution of the nonzero consensus weights.
Table 2 illustrates the consolidated consensus weights allocated by the focus groups to each food insecurity rank by livelihood system.
Figure 2 shows the time evolution of the resulting nonzero consensus weights connected to the original scheme (ACF1) and the proposed algorithm (ACF2).
It has been shown that the algorithm provides convergence even in the case when some nodes may be unstable, owing to a proper choice of the consensus weights.
Sufficient conditions have been obtained to judge the distributed detectability of the networked system, i.e., the existence of filter gains which ensure an asymptotically stable error dynamic given a specific choice of consensus weights.
It can be seen that the main difference between the algorithms is in the consensus weights connected to the nodes that do not have measuring nodes in their neighborhoods.
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