Our algorithms are of polynomial complexity.
该算法具有多项式复杂度。
The fact that it is impossible to find the global optimum in polynomial complexity has been proved.
理论上已经证明要在多项式时间复杂度内对这一类问题找到全局最优解是不可能的。
An algorithm with polynomial complexity was presented to generate the public part of the process from its private one.
设计了一个具有多项式时间复杂度的算法从流程私有部分自动生成相应的公开部分。
The computational complexity of the improved algorithm approaches polynomial complexity, much less than 2 N ( N is the vertex number of a graph).
后者的计算时间复杂性远远低于2N（N为图的顶点数） ，已接近于多项式时间复杂性。
No-wait flow shop problem is one of flow shop problems, and is a typically NP-complete problem, which means that it is impossible to find the global optimum in polynomial complexity.
无等待问题是流水车间调度中的一种，是一类典型的NP完全问题，已被证明在多项式时间内得不到最优值。
For both problems, we study their computational complexity and present optimal algorithms or polynomial time approximation algorithms.
并且对这两类问题都研究了他们的计算复杂性并给出了最优算法或者多项式时间近似算法。
Accordingly, this paper offered optimized algorithm for reduction of knowledge, of which time complexity was polynomial.
在此基础上提出了优化的知识约简算法，该算法的时间复杂度是多项式的。
The method with computation complexity of polynomial order, has been successfully applied to the real-time analysis of signals in mobile ECG telemonitoring systems.
该算法具有多项式级的计算复杂度，已成功应用于移动式远程心电监护系统ECG信号的实时分析。
By using Newton direction and centering direction, we establish a feasible interior point algorithm for monotone linear complementarity problem and show that this method is polynomial in complexity.
利用牛顿方向和中心路径方向，获得了求解单调线性互补问题的一种内点算法，并证明该算法经过多项式次迭代之后收敛到原问题的一个最优解。
The bit - operation complexity of the fast exponential algorithm is polynomial.
快速指数算法的比特运算复杂度是多项式的。
The algorithm's complexity of calculation is polynomial in a speciftc statistic's sense.
算法在统计意义下为多项式时间复杂度。
This paper presents a new dependence difference inequality test algorithm for two-dimensional arrays, and proves that the time complexity of the algorithm is polynomial.
给出了二维数组的体差不等式测试算法，并证明二维数组的体差不等式测试算法具有多项式时间复杂度。
After that we study on the ordered decision table and propose a new heuristic attribute reduction algorithm based on dominance matrix, whose time complexity is polynomial.
再次，对有序决策表进行了研究，提出了一种基于优势矩阵的启发式属性约简算法。
Note: Your solution should be in polynomial time complexity.
注意：你的解法应该满足多项式时间复杂度。
Therefore, there is no algorithm with polynomial computational complexity that guarantees optimal motion vectors.
因此，没有一个多项式(计算的复杂性)算法可以保证最优运动向量。
The complexity of DSAFO is bounded between quadratic and cubic polynomial time.
DSAFO算法具有不错的时间复杂度：介于平方和三次方之间。
The complexity of DSAFO is bounded between quadratic and cubic polynomial time.
DSAFO算法具有不错的时间复杂度：介于平方和三次方之间。
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