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基于二次型的CNN全局渐近稳定性研究
引用本文:张小红,李德音.基于二次型的CNN全局渐近稳定性研究[J].计算机科学,2013,40(1):262-265.
作者姓名:张小红  李德音
作者单位:(江西理工大学信息工程学院 赣州341000)
基金项目:国家自然科学基金(11062002);江西省自然科学基金(2010GZS0083);江西省教育厅科技项目(GJJ11470)资助
摘    要:细胞神经网络稳定性目前已经在图像处理、视频通信和最优控制等领域得到了一定的应用,因此进行稳定性的研究具有重要的意义,如何选择合理的参数模板是研究稳定性的关键问题。运用Lyapunov第二方法对细胞神经网络的全局渐近稳定性进行分析,通过构造出一个较好的Lyapunov函数来得到判定系统全局渐近稳定的一组新的充分条件。该条件改进了已有的结论,进一步推导和完善了系统全局渐近稳定平衡点为原点时的充分条件,经过数值仿真实验验证了其有效性和可行性。

关 键 词:细胞神经网络  全局渐近稳定  Lyapunov函数  二次型矩阵

Research of Global Asymptotic Stability for CNN Based on Quadratic Form
ZHANG Xiao-hong,LI De-yin.Research of Global Asymptotic Stability for CNN Based on Quadratic Form[J].Computer Science,2013,40(1):262-265.
Authors:ZHANG Xiao-hong  LI De-yin
Affiliation:(Faculty of Information Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China)
Abstract:Stability of cellular neural networks is significant because it has been used in a certain application areas as im}r ge processing, video communication, optimal control and so on. How to choose a reasonable template of the parameters is the key issue of stability researches. Lyapunov second method was used to analyze the global asymptotic stability of cellular neural networks, and a better I_yapunov function was constructed to receive a new sufficient condition for deter- mining the global asymptotic stability of the system. The condition improves previous results and further derives a suffi- cicnt condition when original point is equilibrium point. Numerical simulations show their effectiveness and feasibility.
Keywords:Cellular neural networks(CNN)  Global asymptotic stability  Lyapunov function  Quadratic form matrix
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