Sentence examples for computing the solution from inspiring English sources

A major point about the nonlinear difference schemes is to obtain reliable and efficient computational methods for computing the solution.

We propose a novel formulation to efficiently exploit the low (or non-standard) precision number representation of some computer architectures when computing the solution to constrained LQR problems, such as those that arise in predictive control.

In the previous work on rank-2 NMF [32] that takes a term-document matrix as input in the context of text clustering, sparse dense matrix multiplication (SpMM) was the main computational bottleneck for computing the solution.

We have chosen (theta=0.5) in each case for computing the solution of PDE (1), and all the computations were performed using MATLAB.

There are several numerical techniques available for computing the solution.

Various algorithms for computing the solution of (1.1) are proposed.

The Greedy scheme computes the solution to the static model in every time slot.

The inner loop computes the solution of the upper bounded problem.

The Saulyev's finite difference techniques are used to compute the solution.

Furthermore, most numerical methods which compute the solution of IVPs cannot handle systems with uncertain parameters.

The method computes the solution 100 times faster than standard numerical approaches.