具有时滞的双向联想记忆(BAM)的神经网络的全局动力学行为

周进; 刘曾荣; 向兰

具有时滞的双向联想记忆(BAM)的神经网络的全局动力学行为

周进^1,2,3,
刘曾荣³,
向兰⁴

1.
河北工业大学应用数学研究所,天津 300130;2.复旦大学数学研究所,上海 200433;3.上海大学数学系,上海 200436;4.河北工业大学应用物理系,天津 300130

基金项目: 国家自然科学基金资助项目(60474071;10171061);中国国家博士后科学基金资助项目(20040350121);河北省教委科研计划资助项目(2003103);河北省高校应用数学与物理重点学科建设资助项目

详细信息

作者简介:
周进(1963- ),男,重庆人,教授,博士(联系人.Tel:+86-21-55073261;Fax:+86-22-26543322;E-mail:jinzhou@fudan.edu.cn).

中图分类号: O175；TN911
计量
- 文章访问数: 2796
- HTML全文浏览量: 180
- PDF下载量: 945
- 被引次数: 0
出版历程
- 收稿日期: 2003-07-04
- 修回日期: 2004-11-30
- 刊出日期: 2005-03-15

Global Dynamics of Delayed Bidirectional Associative Memory (BAM) Neural Networks

1.
Institute of Applied Mathematics, Hebei University of Technology, Tianjin 300130, P. R. China;

摘要

摘要: 在没有假定关联函数的光滑性,单调性和有界性的条件下,应用Liapunov泛函方法和矩阵代数技术,得到具有常数传输时滞的双向联想记忆(BAM)的神经网络模型平衡点存在性和全局指数稳定性的一些新的充分条件,这些条件可以由网络参数,连接矩阵和关联函数的Lipschitz常数所表示的M矩阵来刻化．这些结果不仅是简单和实用的,而且相对于已有文献的结果具有较少的限制和更易于验证．
- 双向联想记忆(BAM) /
- 神经网络 /
- 全局指数稳定 /
- Liapunov泛函
Abstract: Without assuming the smoothness, monotonicity and boundedness of the activation functions, some novel criteria on the existence and global exponential stability of equilibrium point for delayed bidirectional associative memory (BAM) neural networks are established by applying the Liapunov functional methods and matrix-algebraic techniques. It is shown that the new conditions presented in terms of a nonsingular M matrix described by the networks parameters, the connection matrix and the Lipschitz constant of the activation functions, are not only simple and practical, but also easier to check and less conservative than those imposed by similar results in recent literature.
- bidirectional associative memory (BAM) /
- neural network /
- global exponential stability /
- Liapunov function

HTML全文

参考文献(16)

[1]	Mohamad S.Global exponential stability in continuous-time and discrete-time delayed bidirectional neural networks[J]Physica D,2001,159(3):233—251.
[2]	Liao X F,Yu J B,Chen G.Novel stability criteria for bidirectional associative memory neural networks with time delays [J].International Journal of Circuit Theory and Applications,2002,30(3):519—546. doi: 10.1002/cta.206
[3]	Kosko B. Bidirectional associative memories[J]. IEEE Transactions on Systems,Man,and Cybernetics,1988,18(1):49—60. doi: 10.1109/21.87054
[4]	Kosko B. Unsupervised learning in noise[J].IEEE Transactions on Neural Networks,1990,1(1):44—57. doi: 10.1109/72.80204
[5]	Kosko B. Structural stability of unsupervised learning in feedback neural networks[J].IEEE Transactions on Automatic Control,1991,36(5):785—790. doi: 10.1109/9.85058
[6]	Maundy B,Masry E. A switched capacitor bidirectional associative memory[J].IEEE Transactions on Circuits and Systems,1990,37(12):1568—1572. doi: 10.1109/31.101281
[7]	Gopalsamy K,He X Z. Delay-independent stability in bidirectional associative memory networks[J].IEEE Transactions on Neural Networks,1994,5(7):998—1002. doi: 10.1109/72.329700
[8]	Liao X F,Wong K W,Yu J B. Novel stability conditions for cellular neural networks with time delay[J].International Journal of Bifurcation and Chaos,2001,11(12):1835—1864. doi: 10.1142/S0218127401003097
[9]	Morita M. Associative memory with non-monotone dynamics [J].Neural Networks,1993,6(1):115—126. doi: 10.1016/S0893-6080(05)80076-0
[10]	Yoshizawa S,Morita M,Amari S. Capacity of associative memory using a non-monotonic neuron networks[J].Neural Networks,1993,6(2):167—176. doi: 10.1016/0893-6080(93)90014-N
[11]	Kennedy M P,Chua L O. Neural networks for nonlinear programming[J].IEEE Transactions on Circuits and Systems,1988,35(4):554—562. doi: 10.1109/31.1783
[12]	ZHOU Jin,LIU Zeng-rong,CHEN Guan-rong. Dynamics of delayed periodic neural networks[J].Neural Networks,2004,16(1):87—101.
[13]	ZHOU Jin,CHEN Tian-ping,XIANG Lan. Robust synchronization of coupled delayed recurrent neural networks,Advances in Neural Networks-ISNN[A].Lecture Notes in Computer Science[C].Berlin Heidelberg,New York:Springer-Verlag,2004,3173(1):144—149.
[14]	CHEN Guan-rong,ZHOU Jin,LIU Zeng-rong. Global synchronization of coupled delayed neural networks and applications to chaotic CNN models [J].International Journal of Bifurcation and Chaos,2004,14(7):2229—2240. doi: 10.1142/S0218127404010655
[15]	向兰，周进，刘曾荣，等.具有周期输入Hopfield型神经网络的全局渐近性质[J].应用数学和力学，2002,23(12):1220—1226.
[16]	Hale J K.Introduction to Functional Differential Equations [M].2nd Edition.New York:Berlin Heidelberg:Springer-Verlag,1977.

施引文献

资源附件(0)

访问统计

计量

文章访问数: 2796
HTML全文浏览量: 180
PDF下载量: 945
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

具有时滞的双向联想记忆(BAM)的神经网络的全局动力学行为

作者简介:
周进(1963- ),男,重庆人,教授,博士(联系人.Tel:+86-21-55073261;Fax:+86-22-26543322;E-mail:jinzhou@fudan.edu.cn).

计量

Global Dynamics of Delayed Bidirectional Associative Memory (BAM) Neural Networks

计量

目录

留言板

具有时滞的双向联想记忆(BAM)的神经网络的全局动力学行为

作者简介: 周进(1963- ),男,重庆人,教授,博士(联系人.Tel:+86-21-55073261;Fax:+86-22-26543322;E-mail:jinzhou@fudan.edu.cn).

计量

出版历程

Global Dynamics of Delayed Bidirectional Associative Memory (BAM) Neural Networks

计量

出版历程

目录

作者简介:
周进(1963- ),男,重庆人,教授,博士(联系人.Tel:+86-21-55073261;Fax:+86-22-26543322;E-mail:jinzhou@fudan.edu.cn).