1) GNCP
广义互补问题
1.
The weak regularity is a sufficient and necessary condition for the convergence of Newton-type method for solving the generalized nonlinear complementarity problem(GNCP).
弱正则性是用Gauss-Newton迭代算法求解广义互补问题超线性收敛的一个充分而必要的条件。
2.
In this paper, we consider the generalized complementarity problems (GNCP), and give some constrained optimization reformulations of it.
对于广义互补问题 ,本文给出了它的约束优化问题的两种转化形式 ,讨论了它们的 KKT点为原问题的解的充分条
3.
In Chapter 2, we mainly establish the error estimation of the GNCP.
本文主要研究多面体锥上的广义互补问题(GNCP)的误差界估计,并提出了一类新的求解GNCP的算法。
2) generalized nonlinear complementarity problems
广义互补问题
1.
The generalized nonlinear complementarity problems are the extension of the classical nonlinear complementarity problems.
广义互补问题是互补问题的推广，它在工农业生产等实际问题中有重要的应用。
3) generalized complementarity problem
广义互补问题
1.
Based on a semi smooth equations reformulation of the generalized complementarity problem,a new algorithm is presented.
基于广义互补问题的半光滑方程组变形 ,给出了求解广义互补问题的一种新算法 。
5) Complementary conformal perfectly matched layers
互补共形匹配层
1.
Study of complementary conformal perfectly matched layers;
互补共形匹配层研究(英文)
6) general linear complementarity problem
广义线性互补问题
1.
A gradient-based neural network for the general linear complementarity problem;
解广义线性互补问题的一个基于梯度的神经网络模型
2.
In this paper,a smooth merit function is constructed for general linear complementarity problem(GLCP),which possesses fine coercive property.
本文构造了广义线性互补问题的一个光滑价值函数,该函数具有良好的微分性质。
3.
A nongradient neural network is presented for solving a kind of the general linear complementarity problem.
给出求解一类广义线性互补问题的一个非梯度的神经网络模型。
补充资料：广义特征值问题数值解法
见代数特征值问题数值解法。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条