| 解二次极大极小的时变时滞神经网络 |
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| 引用本文： | 张慧霞,高兴宝.解二次极大极小的时变时滞神经网络[J].云南师范大学学报(自然科学版),2009,29(5):29-33. |
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| 作者姓名： | 张慧霞 高兴宝 |
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| 作者单位： | 陕西师范大学数学与信息科学学院,陕西,西安,710062 |
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| 基金项目： | 国家自然科学基金资助项目，陕西省自然科学基础研究计划 |
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| 摘 要： | 通过鞍点定理和投影理论,提出了一个解二次极大极小问题的变时滞神经网络。利用泛函微分方程理论,给出了确保该变时滞神经网络全局指数稳定的充分条件。由于稳定性分析中不需要原极大极小问题的凸性,该网络可以用来求解一类非凸优化问题。仿真实例验证了理论的正确性和网络的性能。
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| 关 键 词： | 时变时滞 二次极大极小 指数稳定性 |
A Class of Neural Network With Time-varying Delays for Solving Quadratic Maximin Problem |
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| ZHANG Hui-xia,GAO Xing-bao.A Class of Neural Network With Time-varying Delays for Solving Quadratic Maximin Problem[J].Journal of Yunnan Normal University (Natural Sciences Edition),2009,29(5):29-33. |
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| Authors: | ZHANG Hui-xia GAO Xing-bao |
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| Institution: | ZHANG Hui - xia, GAO Xing - bao (College of Mathematics and Information Science ,Shaanxi Normal University ,Xi＇an,710062 ,P. R. China) |
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| Abstract: | In this paper, a neural network model with time -varying delays is proposed to solve a class of maximin problems by employing the saddle point theorem and projection theory. The sufficient conditions are derived to ensure the global exponential stability of the delayed neural network by the theory of functional differential equations. Since the stability of the neural network don＇ t require the convexity of the original maximin problem, the obtained results can be applied to solve a class of nonconvex optimization problem. Finally, numerical examples are presented to demonstrate the validity of the obtained results and the performance of this network. |
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| Keywords: | Time -varying delays Quadratic maximin Global exponential stability |
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