Sentence examples for algorithm termination from inspiring English sources

These algorithms deal well with the leader election problem, and every Voronoi area will have only a leader after algorithm termination.

On the other hand, in the sub-problem of point spread function estimation, the algorithm termination condition is ‖h(l + 1) − h(l)‖/‖h(l)‖ ≤ 10−3.

The improved heuristic with probabilistic color selection using truncated geometric distribution based on node degree ranking reduces the algorithm termination time.

The projection data under under different signal-to-noise ratios 20dB and 40dB is shown in Fig. 2. The selected sparse wavelet transform is db20 wavelet, and the decomposition level is 2. The iterative algorithm termination condition is ( {leftVert {mathbf{x}}_{k+1}-{mathbf{x}}_krightVert}_2^2/{leftVert {mathbf{x}}_{k+1}rightVert}_2^2le 2times {10}^{-6} ).

Zhang et al. [ 16] used a primal-dual interior-point approach, which does not need a regularisation weight, and employed an algorithm termination scheme which can be noise dependent.

In the proposed algorithm, the termination condition is modified in such a way that it is satisfied if and only if the best distances of all PU partitions are equal to 0 simultaneously, indicating that the refinement process is completely finished when all PUs have their search centers as the best matches.

Further, to confirm the robustness of the M-BLEA, we present the final (optimized) upper level design variables attained by both algorithms at termination, in each of the three independent runs.

If the algorithm reaches the termination condition, the result is output; otherwise, the cycle of k from 1 to M is performed, where M is the maximum number of iterations.   5.

To verify the efficiency of the proposed CU splitting early termination algorithm, we conduct comprehensive experiments by comparing the proposed algorithm with HEVC reference software HM6.0.

We use our proposed fast intra-mode decision and CU partition early termination algorithm on HM16.12 to evaluate the effectiveness of the algorithm.

We also restructure the algorithm with efficient termination criteria to achieve the convergence on all the datasets and to improve the reliability of selected set of features.