摘要
借助变分不等式和Kuhn-Tucker条件,构造了一类投影神经网络求解线性约束的退化凸二次规划问题.与已有的求解退化凸规划问题的神经网络系统相比,系统的适用范围更广;在理论方面,系统是全局收敛的;数值实例显示了所得结论的有效性和正确性.
By making use of variational inequality and Kuhn-Tucker conditions, we develop a projection neural network for solving degenerate quadratic programming problems with general linear constraints. Compared with the existing neural networks for solving degenerate convex quadratic program, the proposed neural network has a wider domain for implementation. In the theoretical aspects, the proposed neural network is shown to have global convergence. Illustrative examples show that the proposed neural network is effective and correct.
出处
《五邑大学学报（自然科学版）》
CAS
2009年第1期57-62,共6页
Journal of Wuyi University(Natural Science Edition)
关键词
退化凸二次规划
投影神经网络
变分不等式
K-T条件
全局收敛
degenerate convex quadratic program
projection neural network
variational inequality
Kuhn-Tucker conditions
global convergence
