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。
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。
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 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。
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。
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。
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。
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。
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