摘要
根据人工神经网络的基本优化机理 ,提出了一种基于 L agrange函数的适合于求解二次规划问题的神经网络模型 ,研究了该神经网络的稳定性和收敛性 ,探讨了提高网络优化计算效率的神经优化策略 ,仿真结果证明了该神经网络能有效地求解二次规划问题 .
According to the basic optimization principle of artificial neural networks, a Lagrange function based neural network model approach appropriate for quadratic programming problems is given. Stability and convergence of the neural network are investigated. Neural optimization strategy to improve the neural computing efficiency is studied. Simulation demonstrates that these neural networks can effectively solve quadratic programming problems.The new network is easy to construct with circuits, capable of achieving the exact solution.
出处
《武汉大学学报（理学版）》
CAS
CSCD
北大核心
2001年第3期347-350,共4页
Journal of Wuhan University:Natural Science Edition
基金
冶金工业部科研基金资助项目 ( 1995 -2 42 )
