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1.
Global robust asymptotic stability analysis of uncertain switched Hopfield neural networks with time delay in the leakage term 总被引:1,自引:0,他引:1
P. Balasubramaniam V. Vembarasan R. Rakkiyappan 《Neural computing & applications》2012,21(7):1593-1616
This paper deals with the problem of delay-dependent global robust asymptotic stability of uncertain switched Hopfield neural networks (USHNNs) with discrete interval and distributed time-varying delays and time delay in the leakage term. Some Lyapunov––Krasovskii functionals are constructed and the linear matrix inequality (LMI) approach are employed to derive some delay-dependent global robust stability criteria which guarantee the global robust asymptotic stability of the equilibrium point for all admissible parametric uncertainties. The proposed results that do not require the boundedness, differentiability, and monotonicity of the activation functions. Moreover, the stability behavior of USHNNs is very sensitive to the time delay in the leakage term. It can be easily checked via the LMI control toolbox in Matlab. In the absence of leakage delay, the results obtained are also new results. Finally, nine numerical examples are given to show the effectiveness of the proposed results. 相似文献
2.
Hongyi Li Bing Chen Qi Zhou Weiyi Qian 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2009,39(1):94-102
This paper is concerned with the problem of the robust stability of nonlinear delayed Hopfield neural networks (HNNs) with Markovian jumping parameters by Takagi-Sugeno (T-S) fuzzy model. The nonlinear delayed HNNs are first established as a modified T-S fuzzy model in which the consequent parts are composed of a set of Markovian jumping HNNs with interval delays. Time delays here are assumed to be time-varying and belong to the given intervals. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality approach, stability conditions are proposed in terms of the upper and lower bounds of the delays. Finally, numerical examples are used to illustrate the effectiveness of the proposed method. 相似文献
3.
Robust stability of uncertain fuzzy BAM neural networks of neutral-type with Markovian jumping parameters and impulses 总被引:1,自引:0,他引:1
In this paper, the problem of neutral-type impulsive bidirectional associative memory neural networks (NIBAMNNs) with time delays are first established by a Takagi-Sugeno (T-S) fuzzy model in which the consequent parts are composed of a set of NIBAMNNs with interval delays and Markovian jumping parameters (MJPs). Sufficient conditions to check the robust exponential stability of the derived model are based on the Lyapunov-Krasovskii functionals (LKFs) containing some novel triple integral terms, Lyapunov stability theory and employing the free-weighting matrix method. The delay-dependent stability conditions are established in terms of linear matrix inequalities (LMIs), which can be very efficiently solved using Matlab LMI control toolbox. Finally, numerical examples and remarks are given to illustrate the effectiveness and usefulness of the derived results. 相似文献
4.
针对一类不确定中立型时变时滞Hopfield神经网络的鲁棒稳定性问题, 构造了一个新Lyapunov-Krasovskii泛函, 并结合自由矩阵方法和牛顿—莱布尼茨公式, 得到了新的时滞相关稳定性判据. 该判据考虑了中立型时变时滞Hopfield神经网络中的参数不确定性, 所得结果以线性矩阵不等式(Linear matrix inequality, LMI)的形式给出, 容易验证. 最后, 通过两个数值算例验证了该结果的有效性及可行性. 该判据对丰富与完善中立型神经网络的稳定性理论体系, 具有积极的意义. 相似文献
5.
This paper considers the design of state estimator for Takagi?CSugeno (T?CS) fuzzy neural networks with mixed time-varying interval delays. The mixed time-delays that consist of both the discrete time-varying and distributed time-delays with a given range are presented. The activation functions are assumed to be globally Lipschitz continuous. By using the Lyapunov-Krasovskii method, a linear matrix inequality (LMI) approach is developed to construct sufficient conditions for the existence of admissible state estimator such that the error-state system is exponentially globally stable. To avoid complex mathematical derivations and conservative results, a new hybrid Taguchi-genetic algorithm method is integrated with a LMI method to seek the estimator gains that satisfy the Lyapunov-Krasovskii functional stability inequalities. The proposed new approach is straightforward and well adapted to the computer implementation. Therefore, the computational complexity can be reduced remarkably and facilitate the design task of the estimator for T?CS fuzzy neural networks with time-varying interval delays. Two illustrative examples are exploited in order to illustrate the effectiveness of the proposed state estimator. 相似文献
6.
ABSTRACT In this paper, we study the robust H ∞ performance for discrete-time T-S fuzzy switched memristive stochastic neural networks with mixed time-varying delays and switching signal design. The neural network under consideration is subject to time-varying and norm bounded parameter uncertainties. Decomposing of the delay interval approach is employed in both the discrete delays and distributed delays. By constructing a proper Lyapunov-Krasovskii functional (LKF) with triple summation terms and using an improved summation inequality techniques. Sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to guarantee the considered discrete-time neural networks to be exponentially stable. Finally, numerical examples with simulation results are given to illustrate the effectiveness of the developed theoretical results. 相似文献
7.
8.
《国际计算机数学杂志》2012,89(10):2001-2015
In this paper, the delay-interval-dependent robust stability is studied for a class of neutral stochastic neural networks with time-varying delays. The time-varying delay is assumed to belong to an interval, which means that the upper bound is known and the lower bound is not restricted to zero. For the neural networks under study, the uncertainty includes polytopic uncertainty and linear fractional norm-bounded uncertainty. Sufficient conditions for the stability of the addressed neutral stochastic neural networks with time-varying delays are established by employing the proper Lyapunov–Krasovskii functional, a combination of the stochastic analysis theory, some inequality techniques and new linear matrix inequality (LMI). Finally, three numerical examples are provided to demonstrate less conservatism and effectiveness of the proposed LMI conditions. 相似文献
9.
Xu-Yang Lou Bao-Tong Cui 《国际自动化与计算杂志》2007,4(3):304-314
This paper deals with the problem of delay-dependent robust stability for a class of switched Hopfield neural networks with time-varying structured uncertainties and time-varying delay.Some Lyapunov-Krasovskii functionals are constructed and the linear matrix inequality(LMI)approach and free weighting matrix method are employed to devise some delay-dependent stability criteria which guarantee the existence,uniqueness and global exponential stability of the equilibrium point for all admissible parametric uncertainties.By using Leihniz-Newton formula,free weighting matrices are employed to express this relationship,which implies that the new criteria are less conservative than existing ones.Some examples suggest that the proposed criteria are effective and are an improvement over previous ones. 相似文献
10.
In this paper, delay-dependent robust stabilization and H∞ control for uncertain stochastic Takagi-Sugeno (T-S) fuzzy systems with discrete interval and distributed time-varying delays are discussed. The purpose of the robust stochastic stabilization problem is to design a memoryless state feedback controller such that the closed-loop system is mean-square asymptotically stable for all admissible uncertainties. In the robust H∞ control problem, in addition to the mean-square asymptotic stability requirement, a prescribed H∞ performance is required to be achieved. Sufficient conditions for the solvability of these problems are proposed in terms of a set of linear matrix inequalities (LMIs) and solving these LMIs, a desired controller can be obtained. Finally, two numerical examples are given to illustrate the effectiveness and less conservativeness of our results over the existing ones. 相似文献
11.
Guoquan Liu Simon X. Yang Yi Chai Wei Feng Wei Fu 《Neural computing & applications》2013,22(2):349-359
This paper deals with the robust stability problem of uncertain stochastic neural networks of neutral-type with interval time-varying delays. The uncertainties under consideration are norm-bounded, and the delay is assumed to be time-varying and belongs to a given interval. By using the Lyapunov-Krasovskill functional method and the linear matrix inequality (LMI) technique, the novel stability criteria are derived in terms of LMI. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed criteria. 相似文献
12.
This paper deals with the global asymptotic stability problem for Hopfield neural networks with time-varying delays. By resorting to the integral inequality and constructing a Lyapunov-Krasovskii functional, a novel delay-dependent condition is established to guarantee the existence and global asymptotic stability of the unique equilibrium point for a given delayed Hopfield neural network. This criterion is expressed in terms of linear matrix inequalities (LMIs), which can be easily checked by utilizing the recently developed algorithms for solving LMIs. Examples are provided to demonstrate the effectiveness and reduced conservatism of the proposed condition. 相似文献
13.
T-S模型提供了一种通过模糊集和模糊推理将复杂的非线性系统表示为线性子模型的方法。研究了时滞Hopfield神经网络的随机稳定性(SFVDHNNs)。首先描述了SFVDHNNs模型,然后用Lyapunov方法研究了SFVDHNNs全局均方指数稳定性,通过可以被一些标准的数值分析方法求解的线性矩阵不等式(LMIs)得出了稳定性标准。 相似文献
14.
In this paper, the Takagi–Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Cohen–Grossberg type bidirectional associative memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by using LMI optimization algorithms to guarantee the asymptotic stability of uncertain Cohen–Grossberg BAM neural networks with time varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples. 相似文献
15.
The robust stability of uncertain neutral systems with mixed time-varying delays is investigated in this paper. The uncertainties under consideration are norm-bounded and time-varying. Based on the Lyapunov stability theory, a delay-dependent stability criterion is derived and given in the form of a linear matrix inequality (LMI). Finally, a numerical example is given to illustrate significant improvement over some existing results. 相似文献
16.
This paper investigates the problem of robust stabilization for genetic regulatory networks with interval time-varying delays,
which are subject to norm-bounded time-varying parameter uncertainties. The time delays including lower and upper bounds of
delay are assumed to appear in both the mRNA and protein. The regulatory functions are assumed to be globally Lipschitz continuous.
The resulting delay-range-dependent robust controller with interval range is designed in terms of improved bounding technique.
A sufficient condition for the solvability of the problem is obtained via a linear matrix inequality (LMI). When this LMI
is feasible, an explicit expression of a desired state feedback controller is also given. The theory developed in this paper
is demonstrated by two numerical examples. 相似文献
17.
In this paper, we investigated synchronisation problem for stochastic Takagi–Sugeno (T-S) fuzzy complex networks model with discrete and distributed time delays. By constructing a new Lyapunov functional and employing Kronecker product, we developed delay-dependent synchronisation criterions. By applying stochastic analysis techniques, we derive starting conditions for synchronisation complex networks of the addressed with mixed time-varying delays and stochastic disturbances are achieved. A numerical examples are provided to demonstrate the effectiveness and usefulness of the proposed results. 相似文献
18.
多智能体系统实现鲁棒一致的时延相关稳定判据 总被引:1,自引:0,他引:1
考虑存在多个时变时延、有限能量扰动以及时变拓扑结构不确定等网络约束条件,给出了多智能体系统实现鲁棒一致性的时延相关稳定判据.首先,利用状态分解将原问题转化为讨论不一致向量系统的鲁棒稳定性;然后,考虑到多个时变时延和动态拓扑,采用构造Lyapunov-Krasovskii泛函的方式分析系统鲁棒稳定性,并利用自由权矩阵方法获得关于非线性矩阵不等式(NLMI)的可行解判据;最后,借鉴求解锥补问题的思想,对NLMI判据进行非线性最小化处理,以得到保守性低、易于求解的LMI稳定判据.数值实例和仿真结果均验证了所提出判据的有效性. 相似文献
19.
Jun Li Manfeng Hu Liuxiao Guo Yongqing Yang Yinghua Jin 《Neural computing & applications》2015,26(2):417-427
This paper is concerned with the stability problem for a class of impulsive neural networks model, which includes simultaneously parameter uncertainties, stochastic disturbances and two additive time-varying delays in the leakage term. By constructing a suitable Lyapunov–Krasovskii functional that uses the information on the lower and upper bound of the delay sufficiently, a delay-dependent stability criterion is derived by using the free-weighting matrices method for such Takagi–Sugeno fuzzy uncertain impulsive stochastic recurrent neural networks. The obtained conditions are expressed with linear matrix inequalities (LMIs) whose feasibility can be checked easily by MATLAB LMI Control toolbox. Finally, the theoretical result is validated by simulations. 相似文献
20.
R. Saravanakumar M. Syed Ali He Huang 《International journal of systems science》2016,47(16):3888-3899
This paper focuses on studying the H∞ state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov–Krasovskii functional are handled by the Jensen’s inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable with H∞ performance. The proposed conditions are represented by linear matrix inequalities. Optimal H∞ norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples. 相似文献