A new delayed projection neural network for solving quadratic programming problems with equality and inequality constraints

A new delayed projection neural network for solving quadratic programming problems with equality and inequality constraints
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一种新的延迟投影神经网络,用于解决具有等式和不等式约束的二次规划问题

DOI:
10.1016/j.neucom.2015.05.006
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发表时间:
2015-11
期刊:
影响因子:
6
通讯作者:
Fengli Ren
Fengli Ren
中科院分区:
计算机科学2区
文献类型:
--
作者:
Chunlin Sha;Hongyong Zhao;Fengli Ren

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本文提出了一种新的延迟投影神经网络,用于求解等式和不等式约束的二次规划问题。与现有的神经网络解决这类问题相比,所提出的神经网络具有更少的神经元和一个层次的结构。进一步证明了连续解的存在唯一性。利用微分不等式技巧,证明了新的神经网络全局指数收敛于最优解。最后,借助于数值方法,通过一些应用的仿真结果表明了所提出的神经网络的有效性。
In this paper, a new delayed projection neural network is presented for solving quadratic programming problems subject to equality and inequality constraints. Compared with the existing neural networks for solving such problems, the proposed neural network has fewer neurons and a one-layer architecture. Further, we demonstrate the existence and uniqueness of the continuous solution. By using differential inequality technique, the new neural network is shown to be globally exponentially convergent to optimal solution. Finally, recurring to the numerical method, simulation results with some applications show the effectiveness of the proposed neural network.
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