Abstract Due to instability being induced easily by parameter disturbances of network systems, this paper investigates the multistability of memristive Cohen-Grossberg neural networks (MCGNNs) under stochastic parameter perturbations. It is demonstrated that stable equilibrium points of MCGNNs can be flexibly located in the odd-sequence or even-sequence regions. Some sufficient conditions are derived to ensure the exponential multistability of MCGNNs under parameter perturbations. It is found that there exist at least ( w + 2 ) l (or ( w + 1 ) l ) exponentially stable equilibrium points in the odd-sequence (or the even-sequence) regions. In the paper, two numerical examples are given to verify the correctness and effectiveness of the obtained results.

中文翻译：

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具有随机参数扰动的忆阻 Cohen-Grossberg 神经网络的指数多重稳定性

摘要 由于网络系统的参数扰动容易引起不稳定，本文研究了随机参数扰动下忆阻Cohen-Grossberg神经网络(MCGNNs)的多重稳定性。结果表明，MCGNNs 的稳定平衡点可以灵活地定位在奇数序列或偶数序列区域。推导出了一些充分条件，以确保参数扰动下 MCGNN 的指数多重稳定性。发现在奇数序列（或偶数序列）区域中至少存在（w+2）l（或（w+1）l）个指数稳定的平衡点。文中通过两个数值算例验证了所得结果的正确性和有效性。