共查询到20条相似文献,搜索用时 15 毫秒
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First, we establish the stochastic LaSalle theorem for stochastic infinite delay differential equations with Markovian switching, from which some criterias on attraction are obtained. Then, by employing Lyapunov method and LaSalle-type theorem established above, we obtain some sufficient conditions ensuring the attractor and stochastic boundedness for stochastic infinite delay neural networks with Markovian switching. Finally, an example is also discussed to illustrate the efficiency of the obtained results. 相似文献
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Novel Robust Stability Criteria for Stochastic Hopfield Neural Networks With Time Delays 总被引:2,自引:0,他引:2
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I. V. Boikov 《Automation and Remote Control》2003,64(9):1474-1487
A stability criterion for the Hopfield neural networks with continuous and discontinuous nonlinearities and operation described by nonlinear differential equations is formulated and is based on the sign of the logarithmic norm of a matrix. 相似文献
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This paper is concerned with the exponential stability analysis problem for a class of uncertain stochastic neural networks
with Markovian switching. The parameter uncertainties are assumed to be norm bounded. Based on Lyapunov–Krasovskii stability
theory and the nonnegative semimartingale convergence theorem, delay-dependent and delay- independent sufficient stability
conditions are established. It is also shown that the result in this paper cover some recently published works. Two examples
are provided to demonstrate the usefulness of the proposed criteria. 相似文献
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《Neural Networks, IEEE Transactions on》2009,20(8):1330-1339
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This paper investigates the problem of the pth moment exponential stability for a class of stochastic recurrent neural networks with Markovian jump parameters. With the help of Lyapunov function, stochastic analysis technique, generalized Halanay inequality and Hardy inequality, some novel sufficient conditions on the pth moment exponential stability of the considered system are derived. The results obtained in this paper are completely new and complement and improve some of the previously known results (Liao and Mao, Stoch Anal Appl, 14:165–185, 1996; Wan and Sun, Phys Lett A, 343:306–318, 2005; Hu et al., Chao Solitions Fractals, 27:1006–1010, 2006; Sun and Cao, Nonlinear Anal Real, 8:1171–1185, 2007; Huang et al., Inf Sci, 178:2194–2203, 2008; Wang et al., Phys Lett A, 356:346–352, 2006; Peng and Liu, Neural Comput Appl, 20:543–547, 2011). Moreover, a numerical example is also provided to demonstrate the effectiveness and applicability of the theoretical results. 相似文献
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In this paper, the stability analysis problem is investigated for stochastic bi-directional associative memory (BAM) neural networks with Markovian jumping parameters and mixed time delays. Both the global asymptotic stability and global exponential stability are dealt with. The mixed time delays consist of both the discrete delays and the distributed delays. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, we employ the Lyapunov–Krasovskii stability theory and the Itô differential rule to establish sufficient conditions for the delayed BAM networks to be stochastically globally exponentially stable and stochastically globally asymptotically stable, respectively. These conditions are expressed in terms of the feasibility to a set of linear matrix inequalities (LMIs). Therefore, the global stability of the delayed BAM with Markovian jumping parameters can be easily checked by utilizing the numerically efficient Matlab LMI toolbox. A simple example is exploited to show the usefulness of the derived LMI-based stability conditions. 相似文献
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Vimal Singh 《Neural Processing Letters》2008,27(3):257-265
A modified form of a recent criterion for the global robust stability of interval-delayed Hopfield neural networks is presented.
The effectiveness of the modified criterion is demonstrated with the help of an example. 相似文献
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延迟离散Hopfield网络的动态特征分析 总被引:3,自引:0,他引:3
神经网络的稳定性被认为是神经网络各种应用的基础.主要利用网络的状态转移方程和能量函数来研究带有延迟项的离散Hopfield神经网络动力学行为.给出了延迟离散Hopfield神经网络收敛于周期小于等于2的极限环的一些充分条件.给出了延迟网络收敛于周期为2和4的特殊极限环的一些充分条件.同时,得到了网络不存在任何稳定点的一些必要条件.所获结果不仅推广了一些已有的结论,而且为网络的应用提供了一定的理论基础. 相似文献
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In this paper, a class of uncertain neutral high-order stochastic Hopfield neural networks with time-varying delays is investigated.
By using Lyapunov-Krasovskii functional and stochastic analysis approaches, new and less conservative delay-dependent stability
criteria is presented in terms of linear matrix inequalities to guarantee the neural networks to be globally robustly exponentially
stable in the mean square for all admissible parameter uncertainties and stochastic perturbations. Numerical simulations are
carried out to illustrate the main results. 相似文献
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通过构造适当的Lyapunov函数,利用Halanay不等式和Young不等式,讨论一类具有变时滞的Hopfield型神经网络的全局指数稳定性.在对网络施加两个不同的神经元激励函数的条件下,导出网络全局指数稳定的一个充分条件,得到的充分条件在实际应用中易于验证,且有较小的保守性,因而对网络的应用和设计具有重要意义.最后,一个数值实例进一步验证结果的正确性. 相似文献
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基于众多领域及生物神经网络本身所存在的脉冲瞬动现象,本文首次提出并研究了带时滞的脉冲型Hopfield神经网络的全局指定稳定性问题,并讨论了其平衡态的存在唯一性。 相似文献
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The robust stability of a class of Hopfield neural networks with multiple delays and parameter perturbations is analyzed. The sufficient conditions for the global robust stability of equilibrium point are given by way of constructing a suitable Lyapunov functional. The conditions take the form of linear matrix inequality (LMI), so they are computable and verifiable efficiently. Furthermore, all the results are obtained without assuming the differentiability and monotonicity of activation functions. From the viewpoint of system analysis, our results provide sufficient conditions for the global robust stability in a manner that they specify the size of perturbation that Hopfield neural networks can endure when the structure of the network is given. On the other hand, from the viewpoint of system synthesis, our results can answer how to choose the parameters of neural networks to endure a given perturbation. 相似文献
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Xun-Lin Zhu Guang-Hong Yang 《Neural Networks, IEEE Transactions on》2008,19(10):1783-1791
This paper studies the problem of stability analysis for neural networks (NNs) with a time-varying delay. Unlike the previous works, the activation functions are assumed to be neither monotonic, nor differentiable, nor bounded. By defining a more general type of Lyapunov functionals, some new less conservative delay-dependent stability criteria are established in terms of linear matrix inequalities (LMIs). Meanwhile, the computational complexity of the newly obtained stability conditions is reduced because less variables are involved. Numerical examples are given to illustrate the effectiveness and the benefits of the proposed method. 相似文献
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In this paper, the problem of delay-dependent exponential stability for fuzzy recurrent neural networks with interval time-varying delay is investigated. The delay interval has been decomposed into multiple non equidistant subintervals, on these interval Lyapunov-Krasovskii functionals (LKFs) are constructed to study stability analysis. Employing these LKFs, an exponential stability criterion is proposed in terms of Linear Matrix Inequalities (LMIs) which can be easily solved by MATLAB LMI toolbox. Numerical example is given to illustrate the effectiveness of the proposed method. 相似文献