Sentence examples for an approximate process from inspiring English sources

Specifically, we consider mappings from the original process to an approximate process defined on a significantly smaller sample space.

Neglecting a set of reactions in the full stochastic process X creates an approximate process X ˜ which matches the behavior of the full process in the mean but deviates from the full process in the fluctuations.

For convenience, in the following proof, we assume that the weak solution is appropriately smooth; otherwise, we can consider the corresponding regularized problem, and the same result can also be obtained through an approximate process (see [15]).

The one by Deena Schmidt and Peter Thomas addresses the problem of finding the optimal complexity reducing mapping from a stochastic process on a graph to an approximate process on a smaller sample space, as determined by the choice of a particular linear measurement functional on the graph.

We consider the problem of finding the optimal complexity reducing mapping from a stochastic process on a graph to an approximate process on a smaller sample space, as determined by the choice of a particular linear measurement functional on the graph.

Here we consider the problem of finding the optimal complexity reducing mapping from a stochastic process on a graph to an approximate process on a smaller sample space, as determined by the choice of a particular linear measurement functional on the graph.

Neglecting a set of reactions E ′ ⊂ E creates an approximate processes, X ˜ ( t ), which matches the behavior of the full process in the mean, but deviates from the full process in the fluctuations.

As noted above, it's a pretty approximate process — really just a threshold confidence level that some object is in the picture.

As a distinction from stochastic dynamic programming, the ordering is generated via a relatively fast approximate process, which involves hierarchic application of the principle of maximization of marginal gain.

Xu et al. [27] formulated the online estimation procedure as an approximate optimization process on a Grassmannian.

Based on the modal truncation method of eigenderivatives and some approximate process, a set of formulations for sensitivity numbers of mean square random dynamic responses is derived.