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As we are working on both binary and average consensus, we need to use it.
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We also apply binary and average consensus algorithms in a random graph.
We consider different shapes of topology for applying the binary and average consensus algorithm.
We apply binary and average consensus algorithms in a distributed sensor network.
To make it clear, we have drawn two graphs to view the edges for binary and average consensus individually.
Assuming an average cluster size, required sample sizes are readily computed for both binary and continuous outcomes, by estimating a design effect or inflation factor.
Both binary and continuous traits were simulated.
Binary consensus and average consensus are two widely used consensus algorithms.
Our main algorithm is basically algorithm 6 and 10 which are our main binary consensus and average consensus.
Each node of the sensor network hold three classes of values which are energy, binary states, and average states.
Contour roughness is computed from the binary image, and average gradient is computed from the edge region.
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