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Global mu-stability of quaternion-valued neural networks with non-differentiable time-varying delays

机译:具有不可微时变时滞的四元数值神经网络的全局mu稳定性

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In the paper, the quaternion-valued neural networks (QVNNs) with non-differentiable time-varying delays are considered. Firstly, by using the method of plural decomposition, we decompose the QVNNs into two complex-valued neural networks. Some sufficient criteria in linear matrix inequality (LMI) form are derived to guarantee the existence and uniqueness of the equilibrium point for considered QVNNs by using the homeomorphism mapping principle of complex domain. Secondly, based on applying the free weighting matrix method and constructing appropriate Lyapunov-Krasovskii functional, several conditions are established in LMIs to ensure the the global mu-stability of QVNNs. Finally, by employing the predictor corrector approach, two numerical examples are provided to show the feasibility and availability of the obtained result. (C) 2017 Elsevier B.V. All rights reserved.
机译:在本文中,考虑了具有不可微时变时滞的四元数值神经网络(QVNN)。首先,通过多元分解的方法,将QVNN分解为两个复数值神经网络。通过使用复域的同胚映射原理,导出了一些足够的线性矩阵不等式(LMI)形式的准则,以保证所考虑的QVNN的平衡点的存在和唯一性。其次,在应用自由加权矩阵法并构建适当的Lyapunov-Krasovskii泛函的基础上,为保证QVNN的全局mu-稳定性,在LMI中建立了一些条件。最后,通过采用预测器校正器方法,提供了两个数值示例来说明所获得结果的可行性和可用性。 (C)2017 Elsevier B.V.保留所有权利。

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