1·When system load increases, the system can still reduce the computing time.
当访问压力增大时，系统降低运算量来提高系统性能。
2·Substructure and static condensation are utilized to reduce computing time.
并通过运用子结构法及静力凝聚法减少计算量。
3·This algorithm only involves the calculation of polynomial, it can save computing time.
这个算法只涉及到多项式计算，可节省机时。
4·Moreover, this method substantially reduce the effort in program design and computing time.
这种方法在程序上易于实现，计算量也小。
5·Numerical results show that parallel UTD algorithm can drastically reduce the computing time.
数值结果表明，并行UTD算法可以大大节省计算时间。
6·The more complex the geometry, the more factors can be modeled but the slower the computing time.
几何形状越复杂，模型需要更多的因素，计算时间则更慢。
7·The computing complexity and computing time of this algorithm is lower than that of existed algorithms.
该算法比已有的块三对角矩阵求逆算法的计算复杂度和计算时间低。
8·The experience shows that computing time is reduced; PSNR is raised and there is no clearly block effecting.
实验表明计算时间有所减少，峰值信噪比有所提高，且图象无明显块效应。
9·Meanwhile, motion prediction can reduce the computing time, and improve the robustness of tracking algorithm.
同时运动预测可以减少算法的计算时间，提高算法的鲁棒性。
10·The computations show the method is convenience to handle with constraints, saves computing time and storage space.
实际计算表明，该法处理约束方便、省机时、省内存。