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
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。
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。
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。