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The stability of delays BAM neural networks with Variable-time and poisson arrival impulses

机译:具有可变时间和泊松到达脉冲的时滞BAM神经网络的稳定性

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In this paper, we consider the globally stability of BAM neural networks with time delays and Random Variable-time Impulses (RVI). RVI denotes the impulses occurring follow Poisson Arrival in time, instead of fixed instants. Under this assumption, the time interval between two successive impulses follows exponential distribution with arrival rate. By simulation, we found that the system will be more stability as the arrival rate gets smaller. Numerical examples are also given to illustrate the effective of our results.
机译:在本文中,我们考虑具有时滞和随机可变时间脉冲(RVI)的BAM神经网络的全局稳定性。 RVI表示在时间上遵循泊松到达而不是固定时刻发生的冲动。在这种假设下,两个连续脉冲之间的时间间隔遵循到达率的指数分布。通过仿真,我们发现随着到达率的减小,系统将更加稳定。数值例子也说明了我们的结果的有效性。

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