Dynamics of a class of nonlinear discrete-time neural networks
作者:
Zhu, HY;Huang, LH*
期刊:
Computers & Mathematics with Applications ,2004年48(1-2):85-94 ISSN:0898-1221
通讯作者:
Huang, LH
作者机构:
[Huang, LH] Hunan Univ, Coll Math & Economet, Changsha 410082, Hunan, Peoples R China.;Nanhua Univ, Coll Math Phys, Hengyang 421001, Hunan, Peoples R China.
通讯机构:
[Huang, LH] H;Hunan Univ, Coll Math & Economet, Changsha 410082, Hunan, Peoples R China.
关键词:
difference system;artificial neural network;delay;convergence;periodicity;DIFFERENTIAL-EQUATIONS;PERIODICITY;DELAYS
摘要:
In this paper, we consider a class of delay difference systems with piecewise constant nonlinearity, which includes the discrete version of an artificial neural network model of two neurons described by differential equations with piecewise constant arguments. Some interesting results are obtained for the periodicity and convergence of solutions of the systems. (C) 2004 Elsevier Ltd. All rights reserved.
语种:
英文
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Convergence and periodicity of solutions for a class of delay difference equations
作者:
Zhu, HY;Huang, LH* ;Liao, XY
期刊:
Computers & Mathematics with Applications ,2004年48(10-11):1477-1484 ISSN:0898-1221
通讯作者:
Huang, LH
作者机构:
[Huang, LH] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China.;Nanhua Univ, Coll Math Phys, Hunan 421001, Peoples R China.
通讯机构:
[Huang, LH] H;Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China.
关键词:
Convergence;Difference equation;Periodicity
摘要:
We derive a class of delay difference equations with piecewise constant nonlinearity. The convergence of solutions and the existence of asymptotically stable periodic solutions are investigated, for such a class of difference equations. © 2004 Elsevier Ltd. All rights reserved.
语种:
英文
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Asymptotic Behavior of a Discrete-time Network Model of Two Neurons
作者:
朱惠延;黄立宏
期刊:
数学研究及应用:英文版 ,2004年24(2):267-272 ISSN:2095-2651
作者机构:
[朱惠延] College of Mathematics & Physics Nanhua University;[黄立宏] College of Mathematics & Econometrics Hunan University
关键词:
神经网络;渐近性;差分系统;分段常数非线性
摘要:
本文考虑的是一类具有分段常数非线性时滞差分系统,该系统可作为二元人工神经网络模型的离散形式.本文得到了系统解的渐近性的一些结果.
语种:
中文
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Convergence of a Neural Network of Two Neurons
作者:
朱惠延;黄立宏;戴斌祥
期刊:
应用基础与工程科学学报 ,2003年11(2):113-121 ISSN:1005-0930
作者机构:
[朱惠延] Department of Mathematics-physics,Nanhua University;[黄立宏; 戴斌祥] College of mathematics and Econometrics,Hunan University
关键词:
二元时滞反馈人工神经网络模型;信号传输函数;收敛性;人工智能
摘要:
讨论了一类二元时滞反馈人工神经网络模型.在假设信号传输函数是分段常数非线性的条件下,得到了该模型解的收敛性质.
语种:
中文
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高等数学课程建设探索与实践
作者:
朱惠延;欧阳自根;刘亚春;廖基定;廖新元
期刊:
数学理论与应用 ,2003年(04):21-23 ISSN:1006-8074
作者机构:
南华大学数理学院;南华大学数理学院 衡阳;421001
关键词:
高等数学课程建设;师资队伍建设;教学方法;手段改革;双语教学;第二课堂
摘要:
本文探索了高等数学课程应适应当今教育要求 ,达到培养学生数学素质和能力的建设思路 ,总结了高等数学课程建设在师资队伍建设 ,教学方法、手段改革 ,高等数学双语教学及开展第二课堂等方面所取得的成果
语种:
中文
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Global stability of cellular neural networks with constant and variable delays
作者:
Li, XM;Huang, LH* ;Zhu, HY
期刊:
NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS ,2003年53(3-4):319-333 ISSN:0362-546X
通讯作者:
Huang, LH
作者机构:
[Huang, LH] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China.;Nanhua Univ, Dept Math, Hengyang 421001, Hunan, Peoples R China.
通讯机构:
[Huang, LH] H;Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China.
关键词:
DCNNs;Global asymptotic stability;Global exponential stability;Variable delay
摘要:
This paper gives new conditions ensuring global asymptotic stability and global exponential stability for cellular neural networks with constant delay and variable delay, respectively. These conditions are derived by using the essence of piecewise linearity of the output function of cellular neural networks and by constructing Lyapunov functions and functionals. Furthermore, these conditions are significantly weaker than those given in existing literature. ©2003 Elsevier Science Ltd. All rights reserved.
语种:
英文
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一类二元人工神经网络模型的渐近性
作者:
朱惠延;黄立宏;陈云新
期刊:
南华大学学报(自然科学版) ,2002年16(1):50-53 ISSN:1673-0062
作者机构:
[黄立宏; 朱惠延] 湖南大学;南华大学 数学与计量经济学院;湖南 长沙410082;数理学院;湖南 衡阳421001
关键词:
二元人工神经网络模型;动力系统;渐近性;时滞;初值;阈值
摘要:
本文讨论了一类具有分段常数不连续信号传递函数的二元人工神经网络动力系统的渐近性质.所获结果表明系统的动力性态取决于初值、时滞及阈值的大小.
语种:
中文
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