Mittag-Leffler stability analysis on variable-time impulsive fractional-order neural networks
Mittag-Leffler stability analysis on variable-time impulsive fractional-order neural networks
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DOI：
10.1016/j.neucom.2016.04.045
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发表时间：
2016-09
期刊：
影响因子：
6
通讯作者：
Xujun Yang;Chuandong Li;Q. Song;Tingwen Huang;Xiaofeng Chen
中科院分区：
文献类型：
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作者：
Xujun Yang;Chuandong Li;Q. Song;Tingwen Huang;Xiaofeng Chen
研究了具有变时间脉冲的分数阶神经网络的Mittag-Leffler稳定性。提出了几个充分提出的条件，理论证明，确保有关模型的每一个解决方案，每一个表面的不连续面相交一次。同时，利用B-等价方法，将具有固定时间脉冲效应的降阶分数阶神经网络看作所研究的原始网络模型的比较系统。此外，一系列充分的标准说明了相同的稳定性之间的性质的变时间脉冲分数阶神经网络和固定时间的替代品，并保证所考虑的模型的稳定性。最后，通过两个仿真实例验证了所得到结果的有效性和可行性.
Mittag–Leffler stability analysis of fractional-order neural networks with variable-time impulses is addressed in this paper. Several well-proposed conditions with theoretical demonstration ensuring that every solution of concerned models intersects each surface of the discontinuities exactly once are provided. Meanwhile, by applying B-equivalence method, the reduced fractional-order neural networks with fixed-time impulsive effects can be regarded as the comparison systems of the investigated original network models. Furthermore, a series of sufficient criteria illustrating the same stability properties between both variable-time impulsive fractional-order neural networks and the fixed-time alternative, and guaranteeing the stability of the considered models are presented. Finally, two simulation examples are presented to demonstrate the efficiency and feasibility of the achieved results.