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Robust Passivity and Stability Analysis of Uncertain Complex-Valued Impulsive Neural Networks with Time-Varying Delays

机译:不确定复合脉冲神经网络与时变延迟的强大稳定性分析

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In this article, we investigate the robust passivity and stability analysis of uncertain complex-valued impulsive neural network (UCVINN) models with time-varying delays. Many practical systems are subject to uncertainty in the real-world environments. As a result, we consider the uncertainty of norm-bounded parameters to achieve more realistic system behaviors. By using appropriate Lyapunov-Krasovskii functionals and integral inequalities, sufficient conditions for the robust passivity and global asymptotic stability of UCVINNs are derived by separating complex-valued neural networks into real and imaginary parts. The criteria are given in terms of linear matrix inequalities (LMIs) that can be checked by the MATLAB LMI toolbox. Finally, numerical simulations are presented to illustrate the merits of the obtained results.
机译:在本文中,我们调查了具有时变延迟的不确定复方脉冲神经网络(UCVINN)模型的鲁棒广播和稳定性分析。许多实际系统受真实环境的不确定性。结果,我们考虑了规范有限参数的不确定性,以实现更现实的系统行为。通过使用适当的Lyapunov-krasovskii功能和积分不等式,通过将复值的神经网络分离成真实和虚部来源的鲁斯维诺斯的鲁棒总作力和全局渐近稳定性的充分条件。根据可以由MATLAB LMI工具箱检查的线性矩阵不等式(LMI)给出了标准。最后,提出了数值模拟以说明所获得的结果的优点。

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