Sentence examples for the problem correspond from inspiring English sources

Further analysis also shows that some subclasses of the problem correspond to a single elementary landscape.

In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling.

The definition of the problem corresponds to the definition of the algorithms parameters: population size, maximum number of evaluations, size of the external file, crossover and mutation rates.

The orders of the fractional derivatives are both between 0 and 1 and therefore the problem corresponds to the subdiffusion case.

So the spectrum of the problem corresponds to the spectrum of the operator and there exist an infinite but countable number of real eigenvalues.

Within the framework of Bayesian inference, the problem corresponds to computing the marginal posterior probability density function (pdf) p(x t |z1 k).

It is to be noted that if we start with an empty set of edges (i.e., E = ∅), the problem corresponds to the inference of a time-varying network.

The problems correspond to the situations when the both midspans are loosened, the both midspan bands are fixed, and one midspan band is fixed and the other is loosened.

First, the constraints of the minimization problem correspond to the energies at the output of the SFBs of the source or the relay.

The solutions to the optimization problem correspond to the maximum expected total reward ζ(c) and the SMDP optimal policy δ∗.

The statistical approach to this problem corresponds to the determination of the optimal sequence of phonemes, (F^*), that maximizes the conditional probability of phonemes, (F), given a sequence of graphemes, (G): begin{aligned} text{ F}^*=arg mathop {max }limits _{ F} {P (F| G).} end{aligned} (1 It is difficult to determine (F^) directly by calculating (P {F| G})) for all possible sequences (F).