具有不可微时变时滞四元数神经网络的全局μ-稳定性
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Global μ-stability of Quaternion-valued Neural Networks with Non-ifferentiable Time-varying Delays
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    摘要:

    稳定性是实值、复值、四元数神经网络在众多领域应用中首要关心的问题,针对具有不可微时变时滞的四元数神经网络的全局μ-稳定性问题,提出了在不要求网络可分解情况下的充分性判据;将四元数神经网络整体考虑,通过构造合适的Lyapunov-Krasovskii泛函,运用自由权矩阵和矩阵不等式等技术,获得了所研究网络平衡点的全局μ-稳定性的充分性条件,给出的稳定性判据是四元数线性矩阵不等式表示的,同时将所得结果与已有的结果进行了对比;最后通过一个数值仿真实例验证了结果的有效性.

    Abstract:

    Stability is the primary concern of real-valued, complexvalued, quaternion-valued neural networks in many applications.In the case where the quaternion-valued neural networks(QVNNs) with non-differential time-varying delays is not required to be separated, the sufficiency criterion of the globalμ-stability problem for networks is proposed.By constructing the appropriate LyapunovKrasovskii functional, using the techniques of freeweight matrix and matrix inequality, the sufficient conditions for the globalμ-stability of the equilibrium point of the network under study are obtained.The linear matrix inequalities global μ-stability criterion is provided in the form of quaternionvalued linear matrix inequality (QVLMI).In addition, the results are compared with the existing results.Finally, a numerical example is also given to illustrate the validity and feasibility of the conclusion.

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刘丽缤, 游星星, 潘和平.具有不可微时变时滞四元数神经网络的全局μ-稳定性[J].重庆工商大学学报(自然科学版),2019,36(5):52-57
LIU Li-bin, YOU Xing-xing, PAN He-ping. Global μ-stability of Quaternion-valued Neural Networks with Non-ifferentiable Time-varying Delays[J]. Journal of Chongqing Technology and Business University(Natural Science Edition),2019,36(5):52-57

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  • 在线发布日期: 2019-10-09
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