Sentence examples for a set of constraining from inspiring English sources
end{aligned} (34) Substituting system (34) along with the equation (32) into (B) and collecting the coefficient of the same power (varphi^{i}), we can obtain a set of constraining equations for (a_{i}) and (b_{i}).
Hence the solution of (B) can be written begin{aligned} &F ( xi ) = a_{0} + a_{1} G + a_{2} G^{2}, & H ( xi ) = b_{0} + b_{1} G.end{aligned} (28) Substituting system (28) along with equation (26) into (B) and collecting the coefficient of the same power (G^{i}) leads to a set of constraining equations for (a_{i}) and (b_{i}).
LP is a method of maximizing or minimizing a linear equation (called the objective function) subject to a set of constraining linear equations and inequalities.
This section derives the schedulability analysis of a set of constrained-deadline fork-join tasks onto a homogeneous multicore platform.
A task set with four tasks is used where one of the tasks is decomposed into a set of constrained-deadline sub-tasks.
In many important design problems, some decisions should be made by finding the global optimum of a multiextremal objective function subject to a set of constrains.
This conceptual object was introduced in the literature [7] to suggest that the CR design problem, from the decision making perspective, is better defined by a set of constrains rather than by a set of degrees of freedom.
Decomposition-based techniques ([9,10,12]) traditionally convert tasks with density greater than one into a set of constrained-deadline sequential sub-tasks, each of which with density no greater than one.
Hypothesis testing was done by computing best trees and per site likelihoods with RAxML (mtRev+G+I) for a set of constrained trees.
In the book Savage presents a set of axioms constraining preferences over a set of options that guarantee the existence of a pair of probability and utility functions relative to which the preferences can be represented as maximising expected utility.
The dimension reduction using RCCE is performed by specifying a set of represented (constrained) species, which in this study is selected using a new Greedy Algorithm with Local Improvement (GALI) (based on the greedy algorithm).
