期刊文献+

具混合时滞神经网络周期解的存在性和稳定性

Stability and Existence of almost Periodic Solution for Networks with Mixed Delays
下载PDF
导出
摘要 避开拓扑度理论的方法,通过利用不等式技巧、矩阵理论和Banach空间的不动点理论,在去掉激活函数有界的条件下,获得周期解的存在性、唯一性和全局指数稳定性的充分条件. Recurrent Cellular Networks with mixed delays were considered. Under the help of matrix theory and fixed point theorem in Banach space, some sufficient conditions ensuring existence, uniqueness as well as global exponential stability of periodic solution are established. Some existing results are improved and extended.
出处 《湖南文理学院学报(自然科学版)》 CAS 2007年第2期43-45,共3页 Journal of Hunan University of Arts and Science(Science and Technology)
关键词 概周期解 指数稳定性 回复式细胞神经网络 Almost periodic solut ion exponential stability Recurrent Cellular Networks
  • 相关文献

参考文献10

  • 1[1]Cao J.New results concerning exponential stability and periodic solution of delayed cellular neural networks[J].physics Letters A,2003,307:136-147.
  • 2[2]Liu Z,Liao L.Existence and global exponential stability and periodic solution of cellar neural networks with timevarying delays[J].J Math Anal Appl,2004,290:247-262.
  • 3[3]Cao J.On exponential stability and periodic solution of CNNS with delays[J].Physics letters A,2000,267:312-318.
  • 4[4]Zhang Y,Peng A,Prahlad V.Absolute periodicity and absolute stability of delayed neural networks[J].IEEE Trans Circuit Syst,2002,49(2):256-261.
  • 5[5]Zhao H.Global asymptotic stability of Hopfield neural network involving distributed delays[J].Neural Networks,2004,17:47-53.
  • 6[6]Zheng Y,Chen T.Global exponential stability of delayed periodic dynamical systems[J].Physics letters A,2004,322:344-355.
  • 7[7]Dowling J E.The stability of dynamical system[M].Philadelphia:SIAM,1976.156-258.
  • 8[8]Berman A,Plemmons R.Nonnegative Matrices in the Mathematical Science[M].New York:Academic Press,1979.78-105.
  • 9[9]Arik S.Analysis of exponential stability of delayed neural networks with time varying delays[J].Neural Networks,2004,17:1 027-1 031.
  • 10[10]Liao X,Li C.LMI approach to asymptotical stability of multi-delayed neural network[J].Phy D,2005,200:139-155.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部