Application of transiently chaotic network in nonlinear constraint optimization problems

被引:0
|
作者
Kang Bo [1 ]
Li Xin-yu [1 ]
Li Yun-xia [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 610054, Peoples R China
关键词
chaos; neural network; nonlinear constraint optimization; Lagrange multiplier;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To deal with the deficiencies of the neural network model based on Hopfield neural network (HNN) for nonlinear constraint optimization problems that is easily trapped in local minimum, a novel optimization network model based on transiently chaotic network (TCNN) is proposed in this paper. This network model that combined with Lagrange multiplier theory has higher ability of searching for globally optimal solutions to the nonlinear constraint optimization problems. Its asymptotic stability is proved and its equilibrium point is the optimal point of the original problem. The simulation results illustrate the effectiveness of this optimal network algorithm.
引用
收藏
页码:1181 / 1184
页数:4
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