| 1. | Approximation of lagrange function
拉格朗日函数近似 |
| 2. | Augmented lagrangian function and approximate optimal solutions in nonlinear programming
非线性规划中的增广拉格朗日函数与近似最优解 |
| 3. | The masses arise from the terms in the lagrangian that have the particles interacting with the higgs field
这些质量来自于拉格朗日函数中，一般粒子与希格斯场的交互作用项。 |
| 4. | Wenxue li put forward a sufficient condition of conditional extreme value with lagrange function , but his proof is wrong
摘要李文学用拉格朗日函数提出求条件极值的充分条件，但他的证明却是错误的。 |
| 5. | When adding an entropy function as regularizing term to the lagrangian function , we obtain a smooth approximate function for m ( x ) , which turns out to be the exponential penalty function
当将熵函数作为正则项加到拉格朗日函数上，我们得到了逐点逼近于m ( x )的光滑函数。经证明，该函数即为指数罚函数。 |
| 6. | This text derives out the sufficient condition again no using lagrange function , but direct eliminating a variable from the side condition to transform conditional extreme value into the unconditional extreme value
本文不用拉格朗日函数，而是直接通过消去一个变量将条件极值转化成无条件极值，重新推导出充分性条件。 |
| 7. | Maximum entropy method is an effective smoothing one for the finite min - max problem , which , by adding shannon ' s informational entropy as a regularizing term to the lagrangian function of min - max problem , yields a smooth function that uniformly approaches the non - smooth max - valued function
极大熵方法是解有限极大极小问题的一种有效光滑化法，它通过在极大极小问题的拉格朗日函数上引进shannon信息熵作正则项，给出一致逼近极大值函数的光滑函数。 |
| 8. | Furthermore , when replacing the entropy function by a general separate multiplier function , we develop a new regularization approach , referred to as lagrangian regularization approach . this approach does not only provide a unified smoothing technique for the non - differentiable m ( x ) and but also offers a unified framework for constructing penalty functions , whereby building a bridge between the penalty functions and the classical lagrangian
该方法不仅提供了统一光滑不可微函数m ( x )和( ? | r _ - ~ m )的办法，而且还给出了一种构造罚函数的统一框架，由此将罚函数与经典拉格朗日函数从对偶空间的角度联系在一起。 |
| 9. | To circumvent the non - differentiable difficulty caused by the positive homogeneously function that is involved in an equivalent unconstrained formulation for general inequality constrained optimization problems , we turn to the classical lagrangian function and redefine m ( x ) by a conic optimization problem with the lagrangian as the objective function
为了克服不可微正齐次函数( ? | r _ - ~ m )给约束优化问题的等价无约束形式求解带来的困难，我们将其目标函数m ( x )重新用一个以经典拉格朗日函数为目标的锥优化问题来表示。 |
| 10. | Furthermore , analytical model for adaptive coded modulation is proposed , through which channel snr switching thresholds with the aim of throughput maximization of adaptive coded modulation are obtained with the method of lagrange , and then the average throughput performance of the adaptive system is obtained
通过建立自适应编码调制研究模型，本文还应用拉格朗日函数法得到了使自适应编码调制系统吞吐量性能最大的信道信噪比转换门限，进而得到自适应系统的平均吞吐量性能。 |
