Sentence examples for procedures which solve from inspiring English sources

At one level, the relative efficiencies of procedures, which solve the same problem, are compared.

In case the dimensionality of the double-mutant fitness matrix W is moderate, the matrix approximation problem can be treated using iterative procedures, which solve the weighted least-squares optimization problem, in which binary weights can be employed to ignore the effects of missing entries [58].

A notable example is the existence of a procedure known as Shor's algorithm which solves the problem \(\sc{FACTORIZATION}\) in polynomial time relative the a model of computation known as the Quantum Turing Machine (see Section 3.4.3).

The data was analysed using the least squares (ls-g(s)) procedure of SEDFIT (Dam & Schuck, 2004), which solves the Lamm equation describing the change of concentration distribution with radial position with time in terms of a distribution of sedimentation coefficients, g(s) vs s, where s is the sedimentation coefficient.

Thereby, we can develop an iterative procedure which completely solves the present nonlinear problem.

This is done through an alternating optimization procedure which simultaneously solves the dual problem of the SVM and finds the optimal transformation metric H. Experiments were performed for object recognition and text categorization tasks.

The theoretical formulation is derived by the improved Fourier series representations and subsequently solved by two procedures which are strong form solution and weak form solution.

In this paper, we suggest and evaluate an optimization procedure which specializes in solving a wide variety of optimization problems.

Due to their special behavior ionic liquids, which resemble high salt concentrations rather than organic solvents, they are a challenge to the analytical procedure, which can be solved with the EZ:faast™ kit.

This fact leads to stiffness problems in the optimization procedure, which are partially solved in [ 4] by using an alternative error objective for the mAb concentration.

To achieve such a goal, a novel dynamic loop gain function based approach is proposed to incorporate with the backstepping control design procedure, which enables us to solve the algebraic loop problem caused by all the existing traditional Nussbaum function based approaches and thus establish system stability.