计算机应用研究2016，Vol.33Issue(11)：3261-3264,3269,5.DOI:10.3969/j.issn.1001--3695.2016.11.014
一种新型拉格朗日神经网络解决非光滑优化问题
Novel Lagrange neural network for nonsmooth optimization problems
摘要
Abstract
To solve the problems that many functions are nonsmooth and fixed penalty term has its disadvantages,this paper used the Clarke’s generalized gradient of the involved functions and Lagrange method,established a gradient system of diffe-rential inclusions.It had a variable penalty term to avoid some disadvantages of fixed penalty term.And the network had a global solution and its trajectory converges to the critical point set of primal problems.Furthermore,if the problem was con-vex,the equilibrium point exactly reconciles the solution of the programming problem.Finally,simulation results illustrate above theoretical finding.关键词
非光滑优化/神经网络/局部利普西斯函数/拉格朗日函数Key words
nonsmooth optimization/neural network/locally Lipschitz function/Lagrange function分类
信息技术与安全科学引用本文复制引用
喻昕,李晨宇,许治健,曾俊彦..一种新型拉格朗日神经网络解决非光滑优化问题[J].计算机应用研究,2016,33(11):3261-3264,3269,5.基金项目
国家自然科学基金资助项目（61462006）；广西自然科学基金资助项目 （）
