A high performance neural network for solving quadratic programming with hybrid constraints

摘要：

A high performance neural network is proposed in this paper for solving quadratic programming problems with hybrid constraints. Comparing with the existing neural networks for solving such problems, the proposed neural network has fewer neurons and an one-layer architecture. The proposed neural network is proven to be global convergence. Furthermore, illustrative examples are given to show the effectiveness of the proposed neural network.

关键词： Neural network Convergence Stability Quadratic programming Positive semidefinite

作者: Xianyun Xu Yongqing Yang Yun Gao

作者单位: School of Science, Jiangnan University, Wuxi 214122, PR China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 3261-3266

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）