共查询到17条相似文献,搜索用时 62 毫秒
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带有时变时滞和同步切换的忆阻神经网络的全局指数稳定性 总被引:1,自引:0,他引:1
本文建立并研究了一类具有时变时滞和不同切换机制的忆阻神经网络.利用李雅普诺夫稳定性理论,得到了该神经网络平衡点一致稳定性的充分条件,该充分条件直接有效地反映了时变时滞对稳定性的影响.数值模拟结果验证了理论结果的有效性. 相似文献
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利用M矩阵理论,同构理论以及不等式技巧,研究了一类变时滞神经网络平衡点的存在性和惟一性问题。同时利用M矩阵理论,反证法以及不等式技巧,得到了变时滞神经网络系统惟一的平衡点的全局指数稳定性的充分条件。通过判断由神经网络的权系数、自反馈函数以及激励函数构造的矩阵是否为M矩阵,即可以检验该变时滞神经网络系统的全局指数稳定性。该判据易于用Matlab进行检验,最后给出一个仿真示例进一步证明了判据的有效性。 相似文献
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在近十几年里,已提出了一类与双向联想记忆相联系的神经网络模型,这些模型推广了单层自联想Hebbian相关器为两层异联想模式匹配器,因而,这类网络在模式识别、信号与图像处理等领域中有广阔的应用前景.研究了带离散时滞杂交双向联想记忆神经网络的收敛特性,利用Halanay型不等式获得了网络全局指数稳定性的充分条件,所得结果是与时滞无关的;已证明利用Halanay型不等式获得的结果改进了由Lyapunov方法获得的结果,而且获得的结果容易判定,并且给出了一个数值例子以说明所得结论的正确性. 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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In this Letter, based on globally Lipschitz continous activation functions, new conditions ensuring existence, uniqueness
and global robust exponential stability of the equilibrium point of interval neural networks with delays are obtained. The
delayed Hopfield network, Bidirectional associative memory network and Cellular neural network are special cases of the network
model considered in this Letter.
This revised version was published online in June 2006 with corrections to the Cover Date. 相似文献
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In this paper, a class of interval general bidirectional associative memory (BAM) neural networks with delays are introduced
and studied, which include many well-known neural networks as special cases. By using fixed point technic, we prove an existence
and uniqueness of the equilibrium point for the interval general BAM neural networks with delays. By using a proper Lyapunov
functions, we get a sufficient condition to ensure the global robust exponential stability for the interval general BAM neural
networks with delays, and we just require that activation function is globally Lipschitz continuous, which is less conservative
and less restrictive than the monotonic assumption in previous results. In the last section, we also give an example to demonstrate
the validity of our stability result for interval neural networks with delays. 相似文献
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针对一类含有离散和分布时延神经网络,在神经激活函数较弱的约束条件下,通过定义一个更具一般性的Lyapunov泛函,使用凸组合技术,得到了新的基于线性矩阵不等式表示的指数稳定性判据.与现有结果相比,这些判据具有较小的保守性.仿真算例表明,得到的结果是有效的且保守性小. 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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In this paper, we are concerned with a class of competitive neural networks with multi‐proportional delays. By applying the Banach fixed point theorem and constructing suitable Lyapunov functions, we obtain new sufficient conditions for the global exponential stability to this class of neural networks, which are easily verifiable. Finally, two examples are given to illustrate the effectiveness of the obtained results. 相似文献
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Exponential Periodicity of Continuous-time and Discrete-Time Neural Networks with Delays 总被引:1,自引:0,他引:1
Exponential periodicity of continuous-time neural networks with delays is investigated. Without assuming the boundedness and
differentiability of the activation functions, some new sufficient conditions ensuring existence and uniqueness of periodic
solution for a general class of neural systems are obtained. Discrete-time analogue of the continuous-time system with periodic
input is formulated and we study their dynamical characteristics. The exponential periodicity of the continuous-time system
is preserved by the discrete-time analogue without any restriction imposed on the uniform discretization step-size. 相似文献
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In this Letter, based on globally Lipschitz continous activation functions, new conditions ensuring existence, uniqueness and global robust exponential stability of the periodic solution of interval-delayed neural networks with periodic input are obtained. All the results obtained are generalizations of some resent results reported in the literature for neural networks with constant input. 相似文献