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Besides, every stochastic error coefficient is decreased effectively by total variance method, comparing with Allan variance method.
This seeding assumption of one case per day was chosen to reliably begin a local epidemic in every stochastic simulation.
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An invertible measure-preserving transformation T: X → X, the so-called shift map, is naturally associated with every stationary stochastic process: Tx= {yi}+∞i = −∞, where yi = xi+1 for all i ∈ Z.
Definition 2.2 (compare with[23]) A stochastically continuous stochastic process is said to be square-mean almost automorphic if for every sequence of real numbers, there exist a subsequence {s n } n∈ℕ and a stochastic process.
Besides, variance is reduced by two orders, and every coefficient of stochastic noise is reduced by one order.
Instead of updating the parameters after every training examples (stochastic gradient descent) or updating the parameters once after all the training examples have been processed (batch gradient descent), this technique speeds up the training process as gradient of loss is averaged over each mini-batch (Table 1).
Once the network model is chosen to be stochastic graphs, every aspect of the network such as path, clique, spanning tree, network measures and sampling algorithms should be treated stochastically.
Every node uses the stochastic algorithm to find out the CH. Figure 1 shows the architecture of the standard LEACH Protocol.
All the subpopulations in a given run had the same value of r with a noise term ε (0<ε<0.2; uniform random distribution) added to r for each subpopulation at every generation, to simulate stochastic variation in population growth rates.
For duplexes containing >35% guanine-cytosine (GC) base pairs, we observed stochastic pauses every 2 3 bp during unwinding.
K denotes the number of state paths sampled in each iteration for every training sequence for stochastic EM training.
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