时滞神经网络全局渐近稳定性条件

利用Liapunov泛函方法,结合矩阵不等式技巧,分析了时滞细胞神经网络(DCNNs)的平衡点存在的唯一性和全局渐近稳定性,保证DCNNs的全局稳定性的一个新的充分判据被得到．所得判据提供了一些参数来适当地弥补了反馈矩阵与时滞反馈矩阵之间所需要的平衡关系．这些判据可以容易被使用来设计和检验全局稳定的网络．此外,所得判据是与时滞参数无关,且比已有文献具有更少的限制．     

随机时滞神经网络系统指数稳定性的新判定准则(英文)

本文主要研究了一类随机时滞神经网络的稳定性条件.利用随机分析技巧和不动点原理,建立了一个关于随机时滞神经网络指数稳定性判定的新的准则.     

时变时滞BAM神经网络系统的指数稳定性分析

利用Lyapunov稳定性理论和线性矩阵不等式技术,得到了保证时变时滞BAM神经网络系统指数稳定性的时滞依赖稳定性准则.所给的准则可用Matlab中的LMI控制工具箱进行验证.仿真实例进一步说明了结果的有效性.     

一类随机时滞递归神经网络的指数稳定性(英文)

本文研究了一类随机时滞递归神经网络的指数稳定性问题.利用非负鞅收敛定理和Lyapunov泛函的方法,获得了这类神经网络矩指数稳定性的新的代数准则,所给代数准则简单易用.一个具体实例用来说明稳定性判别准则的应用.     

一类变时滞Cohen-Grossberg神经网络的全局指数稳定性

研究了一类具变时滞的C ohen-Grossberg神经网络的全局指数稳定性.利用同胚映射理论、Lya-punov函数思想和不等式技巧,给出了平衡点存在唯一性和全局指数稳定性的新的判别准则.     

中立型时滞大系统的稳定性

本文研究非线性中立型有界时滞大系统和非线性中立型无界时滞大系统在C空间中的稳定性,获得了简洁、实用的稳定性代数充分准则。本文还对非线性时滞大系统的稳定性进行了研究,建立起一个高维时滞微分不等式,推广了著名的Halanay时滞微分不等式。     

具有时滞的一般型脉冲神经网络的指数稳定性

讨论具有时滞的一般性脉冲神经网络的稳定性.在不假定激励函数有界或可导的前提下,利用非光滑分析和Lyapunov泛函,得到了这类神经网络系统平衡点的存在唯一性和全局指数稳定性判别准则.作为特例,得到了Hopfield神经网络,时滞细胞神经网络,双向联想记忆神经网络的平衡点的存在唯一性和全局指数稳定性判定定理.     

具有非线性扰动的中立型系统的时滞相关稳定性

本研究了具有非线性扰动的中立型系统鲁棒稳定的时滞相关准则。基于LMI方法，并利用S—过程获得了依赖于时滞的鲁棒稳定性准则，所得结果优于已有结论。最后给出一个实例说明本方法的有效性。     

时滞Hopfield神经网络的全局指数稳定性

讨论带有可变时滞的Hopfield神经网络的全局指数稳定性.在非线性激励函数满足Lipschitz条件的假设下,利用推广的Halanay不等式,Dini导数和分析技巧,建立了这类神经网络系统全局指数稳定的几个判别准则.这些判别准则仅仅依赖于系统的参数.     

一类具有时滞的Cohen-Grossberg神经网络的指数稳定性

考虑一类具有时滞的Cohen-Grossberg神经网络,利用Lyapunov方法和微分不等式理论,得到了其全局指数稳定性的判别准则.该准则引入了更多的参数,更便于系统的设计与分析.     

New stability conditions for neural networks with constant and variable delays

In this paper, by utilizing Lyapunov functional method, we analyze global asymptotic stability of neural networks with constant delays. A new sufficient condition ensuring global asymptotic stability of the unique equilibrium point of delayed neural networks is obtained. Furthermore, based on the method of delay differential inequality, the conditions checking global exponential stability of the equilibrium point of neural networks with variable delays are given. The results extend and improve the earlier publications.     

New stability conditions for neural networks with constant and variable delays

In this paper, by utilizing Lyapunov functional method, we analyze global asymptotic stability of neural networks with constant delays. A new sufficient condition ensuring global asymptotic stability of the unique equilibrium point of delayed neural networks is obtained. Furthermore, based on the method of delay differential inequality, the conditions checking global exponential stability of the equilibrium point of neural networks with variable delays are given. The results extend and improve the earlier publications.     

ASYMPTOTIC STABILITY FOR LINEAR AUTONOMOUS DIFFERENTIAL EQUATION WITH SEVERAL DELAYS

Inmathematicalbiology,therehavebeenmanybio1ogicalmodelsinpopu-1ationdynamcis,ecologyandepidemic,whicharedescribedbyautonomousdelaydifferentialequations.Theasymptoticstabilityofthosen1ode1sisinte-resting,whichhavebeenstudiedbymanyauthors[1-4].Thepurposeoft…     

Positive periodic solutions of nonautonomous delay competitive systems with weak Allee effect

This paper considers a nonautonomous Lotka–Volterra type multispecies competitive system with weak Allee effect and delays. The model has the intraspecific competition terms defined by sign changing functions which depend on population density monotonically and time periodically. An existence theorem of positive periodic solutions is established using the coincidence degree theory. Furthermore, for the case of constant delays, a sufficient condition for the positive periodic solution to be globally attractive is proved with the Lyapunov method so that the system attains permanence.     

Suboptimal control of systems with multiple delays

The application of Pontryagin's maximum principle to the optimization of linear systems with time delays results in a system of coupled two-point boundary-value problems involving both delay and advance terms. The exact solution of this system of TPBV problems is extremely difficult, if not impossible. In this paper, a fast-converging iterative approach is developed for obtaining the suboptimal control for nonstationary linear systems with multiple state and control delays and with quadratic cost. At each step of the proposed method, a linear nondelay system with an extra perturbing input must be optimized. The procedure can be extended for the optimization of nonlinear systems with multiple time-varying delays, provided that some of the nonlinearities satisfy the Lipschitz condition.     

Stability analysis of fuzzy Markovian jumping Cohen–Grossberg BAM neural networks with mixed time-varying delays

In this paper, we investigate the robust stability of uncertain fuzzy Markovian jumping Cohen–Grossberg BAM neural networks with discrete and distributed time-varying delays. A new delay-dependent stability condition is derived under uncertain switching probabilities by Takagi–Sugeno fuzzy model. Based on the linear matrix inequality (LMI) technique, upper bounds for the discrete and distributed delays are calculated using the LMI toolbox in MATLAB. Numerical examples are provided to illustrate the effectiveness of the proposed method.     

具有两个加性输入时滞系统的状态反馈控制

主要考虑了具有两个加性输入时滞的网络化控制系统的状态反馈控制问题.首先考虑具有两个加性时滞的系统稳定性,构造适当的Lyapunov泛函,不需要所有的矩阵正定,只需其整体正定.其次在估计Lyapunov泛函沿系统的导数时,针对时滞范围的不同,引入了不同的松弛矩阵,得出系统保守性较小的稳定条件.在此基础上,研究了系统状态反馈控制,最后得出闭环系统渐近稳定的充分条件,并给出控制器的设计方法.     

A differential game of evasion with delays

A game of evasion (or contact avoidance problem) described by a system of differential equations containing delays in state and control is considered. There is given a sufficient condition for the existence of a strategy which ensures the contact avoidance. A method of constructing such a strategy is presented.     

GLOBAL EXPONENTIAL STABILITY IN HOPFIELD AND BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH TIME DELAYS

Without assuming the boundedness, strict monotonicity and differentiability of the activation functions, the authors utilize the Lyapunov functional method to analyze the global convergence of some delayed models. For the Hopfield neural network with time delays, a new sufficient condition ensuring the existence, uniqueness and global exponential stability of the equilibrium point is derived. This criterion concerning the signs of entries in the connection matrix imposes constraints on the feedback matrix independently of the delay parameters. From a new viewpoint, the bidirectional associative memory neural network with time delays is investigated and a new global exponential stability result is given.     

状态与输出均有滞后的不确定广义系统的非脆弱$H_\infty$控制

针对带有状态滞后的连续广义系统,给出了其广义二次稳定且满足一定H∞性能的充分条件,并利用线性矩阵不等式技术,得到了带有状态滞后和不确定性的连续广义系统的含有控制器增益扰动的鲁棒H∞控制器的设计方法.最后,所举数值例子说明了该方法的应用.