共查询到20条相似文献,搜索用时 593 毫秒
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The global asymptotic stability of impulsive stochastic Cohen–Grossberg neural networks with mixed delays and reaction–diffusion terms is investigated. Under some suitable assumptions and using Lyapunov–Krasovskii functional method, we apply the linear matrix inequality technique to propose some new sufficient conditions for the global asymptotic stability of the addressed model in the stochastic sense. The mixed time delays comprise both the time-varying and continuously distributed delays. The effectiveness of the theoretical result is illustrated by a numerical example. 相似文献
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Global and robust stability of interval Hopfield neural networks with time-varying delays 总被引:3,自引:0,他引:3
In this paper, we investigate the problem of global and robust stability of a class of interval Hopfield neural networks that have time-varying delays. Some criteria for the global and robust stability of such networks are derived, by means of constructing suitable Lyapunov functionals for the networks. As a by-product, for the conventional Hopfield neural networks with time-varying delays, we also obtain some new criteria for their global and asymptotic stability. 相似文献
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The problem of the global asymptotic stability for a class of neural networks with time-varying delays is investigated in this paper, where the activation functions are assumed to be neither monotonic, nor differentiable, nor bounded. By constructing suitable Lyapunov functionals and combining with linear matrix inequality (LMI) technique, new global asymptotic stability criteria about different types of time-varying delays are obtained. It is shown that the criteria can provide less conservative result than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach. 相似文献
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The robust asymptotic stability analysis for uncertain BAM neural networks with both interval time-varying delays and stochastic disturbances is considered. By using the stochastic analysis approach, employing some free-weighting matrices and introducing an appropriate type of Lyapunov functional which takes into account the ranges for delays, some new stability criteria are established to guarantee the delayed BAM neural networks to be robustly asymptotically stable in the mean square. Unlike the most existing mean square stability conditions for BAM neural networks, the supplementary requirements that the time derivatives of time-varying delays must be smaller than 1 are released and the lower bounds of time varying delays are not restricted to be 0. Furthermore, in the proposed scheme, the stability conditions are delay-range-dependent and rate-dependent/independent. As a result, the new criteria are applicable to both fast and slow time-varying delays. Three numerical examples are given to illustrate the effectiveness of the proposed criteria. 相似文献
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This paper concerns the problem of global exponential synchronization for a class of memristor-based Cohen–Grossberg neural networks with time-varying discrete delays and unbounded distributed delays. The drive-response set is discussed. A novel controller is designed such that the response (slave) system can be controlled to synchronize with the drive (master) system. Through a nonlinear transformation, we get an alternative system from the considered memristor-based Cohen–Grossberg neural networks. By investigating the global exponential synchronization of the alternative system, we obtain the corresponding synchronization criteria of the considered memristor-based Cohen–Grossberg neural networks. Moreover, the conditions established in this paper are easy to be verified and improve the conditions derived in most of existing papers concerning stability and synchronization for memristor-based neural networks. Numerical simulations are given to show the effectiveness of the theoretical results. 相似文献
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This paper presents new theoretical results on global exponential stability of cellular neural networks with time-varying delays. The stability conditions depend on external inputs, connection weights and delays of cellular neural networks. Using these results, global exponential stability of cellular neural networks can be derived, and the estimate for location of equilibrium point can also be obtained. Finally, the simulating results demonstrate the validity and feasibility of our proposed approach. 相似文献
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In this paper, we extensively study the global asymptotic stability problem of complex-valued neural networks with leakage delay and additive time-varying delays. By constructing a suitable Lyapunov–Krasovskii functional and applying newly developed complex valued integral inequalities, sufficient conditions for the global asymptotic stability of proposed neural networks are established in the form of complex-valued linear matrix inequalities. This linear matrix inequalities are efficiently solved by using standard available numerical packages. Finally, three numerical examples are given to demonstrate the effectiveness of the theoretical results. 相似文献
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This paper is concerned with a class of nonlinear uncertain switched networks with discrete time-varying delays . Based on the strictly complete property of the matrices system and the delay-decomposing approach, exploiting a new Lyapunov–Krasovskii functional decomposing the delays in integral terms, the switching rule depending on the state of the network is designed. Moreover, by piecewise delay method, discussing the Lyapunov functional in every different subintervals, some new delay-dependent robust stability criteria are derived in terms of linear matrix inequalities, which lead to much less conservative results than those in the existing references and improve previous results. Finally, an illustrative example is given to demonstrate the validity of the theoretical results. 相似文献
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Relaxed stability conditions for delayed recurrent neural networks with polytopic uncertainties 总被引:1,自引:0,他引:1
This paper investigates the problem of stability analysis for recurrent neural networks with time-varying delays and polytopic uncertainties. Parameter-dependent Lypaunov functionals are employed to obtain sufficient conditions that guarantee the robust global exponential stability of the equilibrium point of the considered neural network. The derived stability criteria are expressed in terms of a set of relaxed linear matrix inequalities, which can be easily tested by using commercially available software. Two numerical examples are provided to demonstrate the effectiveness of the proposed results. 相似文献
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This paper aims to analyze global robust exponential stability in the mean square sense of stochastic discrete-time genetic
regulatory networks with stochastic delays and parameter uncertainties. Comparing to the previous research works, time-varying
delays are assumed to be stochastic whose variation ranges and probability distributions of the time-varying delays are explored.
Based on the stochastic analysis approach and some analysis techniques, several sufficient criteria for the global robust
exponential stability in the mean square sense of the networks are derived. Moreover, two numerical examples are presented
to show the effectiveness of the obtained results. 相似文献
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利用拓扑度理论和Liapunov泛函方法讨论了变时滞区间细胞神经网络的全局鲁棒稳定性.给出了实用有效的判定条件,推广了有关文献中的结果. 相似文献
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具有连续分布时滞神经网络的稳定性分析 总被引:5,自引:0,他引:5
本文研究具有连续分布时滞神经网络的平衡点的稳定性问题,利用构造Lyapunov泛函和不等式分析技巧,给出了具有连续分布时滞神经网络全局渐近稳定性的充分条件。 相似文献
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New criteria of almost periodic solution for bam neural networks with delays and impulsive effects 总被引:1,自引:0,他引:1
This paper presents some sufficient conditions for the existence and global exponential stability of the almost periodic solution for impulsive bi-directional associative memory neural networks with time-varying delays by using Lyapunov functional and Gronwall-Bellmans inequality technique. Comparing with known literatures, the results of this paper are new and they complement previously known results. 相似文献
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研究了一类具多比例时滞细胞神经网络的全局指数周期性与稳定性.通过变换y(t)=x(e~t)将具多比例时滞的细胞神经网络变换成具常时滞变系数的细胞神经网络,利用一些分析技巧与构造合适的Lyapunov泛函,得到系统的周期解存在唯一且全局指数周期的时滞依赖的充分条件,判断方法简单易验证.并给出了两个例子及其数值仿真结果以支持所得结论. 相似文献
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In this paper, the synchronization problem for delayed continuous time nonlinear complex neural networks is considered. The
delay dependent state feed back synchronization gain matrix is obtained by considering more general case of time-varying delay.
Using Lyapunov stability theory, the sufficient synchronization criteria are derived in terms of Linear Matrix Inequalities
(LMIs). By decomposing the delay interval into multiple equidistant subintervals, Lyapunov-Krasovskii functionals (LKFs) are
constructed on these intervals. Employing these LKFs, new delay dependent synchronization criteria are proposed in terms of
LMIs for two cases with and without derivative of time-varying delay. Numerical examples are illustrated to show the effectiveness
of the proposed method. 相似文献
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具有时滞的双向联想记忆神经网络的全局渐近稳定性 总被引:1,自引:2,他引:1
双向联想记忆模型是两层异联想网络,本文讨论了具有轴突信号传输时滞的双向联想记忆神经网络的全局渐近稳定性,得出了保证神经网络平衡点稳定的几个充分条件,所得到的结论对于具有时滞的连续双向联想记忆神经网络的设计和应用都是很有意义的。 相似文献