| 1. | We are seeking a stationary point .
我们要寻求的是驻点。 |
| 2. | A cusp is also called a stationary point or point of retrogression gression .
尖点也叫做平稳点或逆行点。 |
| 3. | A stationary point which is neither a local maximum nor a local minimum point is called a saddle point .
一个既不是局部极大点又不是局部极小点的平稳点称为一个鞍点。 |
| 4. | Given a response surface equation in quadratic form , the six sigma black belt will be able to compute the stationary point
给出一个二次方程式形式的响应曲面公式， 6西格玛黑带应能计算出驻点。 |
| 5. | Given data ( not graphics ) , the six sigma black belt will be able to determine if the stationary point is a maximum , minimum or saddle point
给定数据（不是图形） ， 6西格玛黑带应能确定驻点是最大值、最小是还是马鞍点。 |
| 6. | Given data ( not graphics ) , the six sigma black belt will be able to determine if the stationary point is a maximum , minimum or saddle point
译文：给定数据（不是图形） ，六西格玛黑带应该能够确定驻点是最大值、最小值还是承受点。 |
| 7. | Secondly , the stationary points of the lccm cost function are analyzed to demonstrate that the lccma attempts to suppress multipath of the desired user ' s signal rather than exploit it
其次，通过分析代价函数的稳定点，证明lccma算法只是试图抑制期望用户信号的多径，而不是利用它。 |
| 8. | Similar results were generalized to multiobjective programming in ref . 37 , and the equivalent conditions that every stationary point or kuhn - tucker point is a weakly efficient solution were also obtained
文献[ 37 ]将类似的结果推广到多目标规划，并且获得了每个驻点(或k - t点)是弱有效解的等价条件。 |
| 9. | Martin ( ref . 36 ) proved the equivalence between some invexity and the case that every stationary point or kuhn - tucker point is a global minimum point for unconstrained or constrained scalar programming
Martin在文献[ 36 ]中，证明了无约束或约束单目标规划中某类不变凸性与每个驻点(或k - t点)即为全局最优点的等价性。 |
| 10. | Motivated by the above results , the third part of this paper considers the equivalence problems that every stationary point or kuhn - tucker point is an efficient solution . we define i - quasi - invex vector function . , i - strictly quasi - invex vector function and kt - i - strictly quasi invex vector function , and derive the above equivalent condition for unconstrained or constrained multiobjective programming
于是，在本文的第三部分，我们定义了类不变拟凸、类严格不变拟凸、 kt -类严格不变拟凸的向量值函数，并且在无约束或约束多目标规划中，获得了每个驻点(或k - t点)是有效解的等价条件。 |
