%0 Journal Article
%T Neural Network for Nonlinear Programming Problems with Hybrid Constraints<br>求解混合约束非线性规划的神经网络模型
%A TAO Qing
%A REN Fu-xing
%A SUN De-min
%A <br>陶卿
%A 任富兴
%A 孙德敏
%J 软件学报
%D 2002
%I 
%X In this paper, a kind of globally convergent continuous neural network for optimization problems is presented by designing Liapunov function skillfully, it has better function and higher performance. It is capable of solving nonlinear programming problems with the constraints of equality and inequality. The proposed neural network is an extension of Newton deepest decedent method for constraint problems, it can improve the accuracy of the solutions, and its structure is simpler than the existing networks even when it is for solving positive definite quadratic programming problems.
%K nonlinear programming problems
%K neural network
%K energy function
%K global asymptotic stability<br>非线性规划问题
%K 神经网络
%K 能量函数
%K 大范围收敛性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=6339C6CCF1C8C641&yid=C3ACC247184A22C1&vid=FC0714F8D2EB605D&iid=0B39A22176CE99FB&sid=8ED630AD8C61FAE8&eid=85002451B65CE0D1&journal_id=1000-9825&journal_name=软件学报&referenced_num=1&reference_num=18