New type of lagrange nonlinear programming neural network

被引：0
|
作者：
Huang, Yuan-Can [1 ]
机构：
[1] Dept. of Automat. Control, Beijing Inst. of Technol., Beijing 100081, China
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2001年 / 30卷 / 01期
关键词：
Constraint theory - Convergence of numerical methods - Lagrange multipliers - Mathematical models - Nonlinear programming - Optimization - Stability - Theorem proving;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
By modifying the Lagrange multipliers, both equality and inequality constraints can be treated identically. Based on this idea, a new type of Lagrange nonlinear programming neural network is constructed, and the stability and convergence of the neural network are analyzed rigorously. Furthermore, the convergence condition of the network is relaxed by the approach of adding the penalty terms in the Lagrangian function.
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页码：27 / 29
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