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Robust stability analysis of delayed Takagi-Sugeno fuzzy Hopfield neural networks with discontinuous activation functions

机译:具有不连续激活函数的时滞Takagi-Sugeno模糊Hopfield神经网络的鲁棒稳定性分析

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摘要

In this paper, the global robust stability problem of delayed Takagi–Sugeno fuzzy Hopfield neural networks with discontinuous activation functions (TSFHNNs) is considered. Based on Lyapunov stability theory and M-matrices theory, we derive a stability criterion to guarantee the global robust stability of TSFHNNs. Compared with the existing literature, we remove the assumptions on the neuron activations such as Lipschitz conditions, bounded, monotonic increasing property or the assumption that the right-limit value is bigger than the left one at the discontinuous point. Finally, two numerical examples are given to show the effectiveness of the proposed stability results.
机译:在本文中,考虑了具有不连续激活函数(TSFHNN)的时滞Takagi-Sugeno模糊Hopfield神经网络的全局鲁棒稳定性问题。基于Lyapunov稳定性理论和M矩阵理论,我们推导了一种稳定性准则,以保证TSFHNNs的全局鲁棒稳定性。与现有文献相比,我们删除了有关神经元激活的假设,例如Lipschitz条件,有界,单调递增的性质,或者在不连续点处右极限值大于左极限值的假设。最后,给出了两个数值例子来说明所提出的稳定性结果的有效性。

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