Global Robust Passivity Analysis for Stochastic Interval Neural Networks with Interval Time-Varying Delays and Markovian Jumping Parameters

In this paper, the problem of passivity analysis is investigated for stochastic interval neural networks with interval time-varying delays and Markovian jumping parameters. By constructing a proper Lyapunov-Krasovskii functional, utilizing the free-weighting matrix method and some stochastic analysis techniques, we deduce new delay-dependent sufficient conditions, that ensure the passivity of the proposed model. These sufficient conditions are computationally efficient and they can be solved numerically by linear matrix inequality (LMI) Toolbox in Matlab. Finally, numerical examples are given to verify the effectiveness and the applicability of the proposed results.     

具有随机扰动和多重变时滞的神经网络稳定性分析

考虑了一个具有多重时变时滞的随机神经网络的全局渐近稳定性问题.通过构造Lyapunov-Krasovskii函数并运用广义Ito公式,得到了一个充分条件,条件保证了神经网络在随机扰动下的全局均方渐近稳定性.最后通过一个数值实例验证了结果的有效性.     

Stochastic Stability Analysis for Switched Genetic Regulatory Networks with Interval Time-Varying Delays Based on Average Dwell Time Approach

In this article, the problem of stochastic stability analysis for switched stochastic genetic regulatory networks with interval time-varying delays based on average dwell time approach is investigated. By constructing the piecewise Lyapunov-Krasovskii functional, delay-dependent stability conditions are derived by using free-weighting matrix and convex combination approach. The derived stability conditions are expressed in terms of linear matrix inequalities which can be easily solved by using the MATLAB LMI control toolbox. Finally, numerical examples are provided to demonstrate the effectiveness and less conservativeness of the proposed theoretical results.     

随机变时滞模糊神经网络的均方指数稳定性

利用Lyapunov泛函和随机分析的方法,研究了一类具有变时滞随机模糊细胞神经网络的均方指数稳定性,得到了这类神经网络均方指数稳定性的充分条件.数值例子说明了得到的结果的有效性.     

具有混合时滞的区间神经网络的全局指数稳定性

本文研究了一类具有混合时滞的区间神经网络系统的全局指数稳定性.通过选择适当的Lyapunov泛函,运用不等式技巧,得到了用线性矩阵不等式表示的有关的区间神经网络全局指数稳定的充分判据.通过一个数值实例验证了判据的有效性.     

带有时滞的Clifford值神经网络的全局指数稳定性

研究了带有离散时滞和分布时滞的Clifford值递归神经网络的全局指数稳定性问题.首先运用M矩阵的性质和不等式技巧证明了Clifford值递归神经网络平衡点的存在性和唯一性;然后通过数学分析方法,得到了Clifford值递归神经网络全局指数稳定的判定条件;最后数值仿真例子验证了获得结果的有效性.     

具有混合变时滞的脉冲Cohen-Grossberg神经网络的指数同步

该文研究了一类具有混合变时滞的脉冲Cohen—Grossberg神经网络模型的指数同步问题.通过构造适当的Lyapunov函数和利用反证法,得到了简单而有效的指数同步判据.最后,通过一个实例的数值模拟来说明所得结果的有效性.     

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.     

Dynamical Systems with Multiple Time-Varying Delays: Stability and Stabilizability

This paper deals with the class of uncertain systems with multiple time delays. The stability and stabilizability of this class of systems are considered. System robustness is also studied when the norm-bounded uncertainties are considered. LMI delay-dependent sufficient conditions for stability, stabilizability, and system robustness are established to check whether a system of this class is stable and/or stabilizable. Numerical examples are provided to show the usefulness of the proposed results.     

具脉冲混合时滞马尔可夫跳中立型随机神经网络系统指数稳定性

研究了具脉冲和混合时滞马尔可夫跳随机神经网络的鲁棒指数稳定性.通过构造合适Lyapunov-Krasovsii泛函,利用随机Lyapunov稳定性理论,给出并证明了该系统均方指数稳定性的充分条件,所有结果以线性矩阵不等式的形式给,数值算例表明无论脉冲是否发生在马尔可夫跳时刻,给出的稳定性标准都是有效的.     

具有时滞的复杂动态网络的无源性

研究了复杂时滞动态网络的无源性.通过构造适当的Lyapunov泛函,得出了两个使得复杂网络无源的充分条件.最后,通过一个具体的例子及其仿真来阐明得到的条件的有效性.     

Exponential Stability for Time-Delay Systems with Interval Time-Varying Delays and Nonlinear Perturbations

In this paper, the problem of an exponential stability for time-delay systems with interval time-varying delays and nonlinear perturbations is investigated. Based on the Lyapunov method, a new delay-dependent criterion for exponential stability is established in terms of LMI (linear matrix inequalities). Numerical examples are carried out to support the effectiveness of our results.     

Exponential Synchronization of the Linearly Coupled Dynamical Networks with Delays

In this paper,the authors investigate the synchronization of an array of linearly coupled identical dynamical systems with a delayed coupling.Here the coupling matrix can be asymmetric and reducible.Some criteria ensuring delay-independent and delay- dependent global synchronization are derived respectively.It is shown that if the coupling delay is less than a positive threshold,then the coupled network will be synchronized.On the other hand,with the increase of coupling delay,the synchronization stability of the network will be restrained,even eventually de-synchronized.     

The Existence and Global $p$-Exponential Stability of Periodic Solution for Stochastic BAM Neural Networks with Delays

In this paper, we consider a class of stochastic BAM neural networks with delays. By establishing new integral inequalities and using the properties of spectral radius of nonnegative matrix, some sufficient conditions for the existence and global $p$-exponential stability of periodic solution for stochastic BAM neural networks with delays are given. An example is provided to show the effectiveness of the theoretical results.     

带有变时滞延迟和分布延迟的竞争型神经网络周期解在时间尺度上的的全局指数稳定性

In this paper, competitive neural networks with time-varying and distributed delays are investigated. By utilizing Lyapunov functional methods, the global exponential stability of periodic solutions of the neural networks is discussed on time scales. In addition, an example is given to illustrate the effectiveness of the theoretical results.     

无界变时滞神经网络全局稳定性

该文研究了具无界变时滞的时变神经网络的全局稳定性.利用两种不同的分析方法得到了保证这类神经网络全局渐近稳定的一些充分条件.推广和改进了现有文献中常时滞或时滞为零的相应结果.     

带有变化分布时滞的复值神经网络Lagrange稳定性

研究了带有变化分布时滞的复值神经网络Lagrange稳定性问题.通过构造合适的Lyapunov Krasovskii泛函, 并使用矩阵不等式技巧,建立了网络全局指数Lagrange稳定性的判定条件.提供的判据是复值线性矩阵不等式, 能够使用MATLAB软件的YALMIP工具箱快速计算.     

时滞型脉冲神经网络的全局指数稳定性(英文)

对一类含时滞的脉冲神经网络平衡点的存在性和稳定性进行了研究.在不假定激励函数有界、单调或可微而仅假定激励函数Lipschitz连续的条件下,利用压缩映像原理证明了系统平衡点的存在性,利用右上Dini导数的性质并通过构造适当的Lyapunov函数得到了平衡点全局指数稳定的充分条件.文末通过实例说明了所获结论的有效性.     

具有可变时滞的Hopfield型随机神经网络的指数稳定性

研究了具有可变时滞的Ｈｏｐｆｉｅｌｄ型随机种经网络的指数稳定性,应用Ｒａｚｕｍｉｋｈｉｎ定理与 Ｌｙａｐｕｎｏｖ函数,建立了这种神经网络的均方指数稳定与几乎必然指数稳定的两类判据,一类是时 滞相关而另一类是时滞无关．