%0 Journal Article
%T Research of Global Asymptotic Stability for CNN Based on Quadratic Form<br>基于二次型的CNN全局渐近稳定性研究
%A ZHANG Xiao-hong
%A LI De-yin
%A <br>张小红
%A 李德音
%J 计算机科学
%D 2013
%I 
%X 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.
%K Cellular neural networks(CNN)
%K Global asymptotic stability
%K Lyapunov function
%K Quadratic form matrix<br>细胞神经网络
%K 全局渐近稳定
%K Lyapunov函数
%K 二次型矩阵
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=F2F3E0E822DEB5B2C15131D5FE04ECC3&yid=FF7AA908D58E97FA&vid=1371F55DA51B6E64&iid=CA4FD0336C81A37A&sid=30897FA31CA3354D&eid=FDC7AF55F77D8CD4&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0