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Due to their inherent randomness, the run-time behaviour of these algorithms is characterised by a random variable.
Let be a sequence of random variables which is stochastically dominated by a random variable.
Assume that the random variables are stochastically dominated by a random variable.
In these models, the distance between crossovers is modeled by a random variable with some distribution.
The signal shadowing is represented by a random variable with zero mean and standard deviation.
Let ({X_{n}, ngeq1}) be a sequence of random variables which is stochastically dominated by a random variable X.
Let ({X_{n}, ngeq1}) be a sequence of random variables weakly upper bounded by a random variable X.
Suppose that ({ {{X}_{ni}},ige1,nge1 }) is an array of random variables stochastically dominated by a random variable X.
Each point x i is marked by a random variable m i that is uniformly distributed between [0,1].
Let X n, n ∈ N, be random variables, which are stochastically dominated by a random variable X.
Since the estimated value of probability for some intermediate event may have large uncertainty, the uncertainty can thus be characterized by a random variable.
More suggestions(16)
by a dependent variable
by a random unlicensed
by a multiple variable
by a nominal variable
by a single variable
by a forward variable
by a dummy variable
by a random geometric
by a third variable
by a long variable
by a random non-negative
by a Boolean variable
by a binary variable
by a random binary
by a latent variable
by a random rough
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com