The key contribution of this paper is to study the stability analysis of neutral-type Cohen-Grossberg neural networks possessing multiple time delays in the states of the neurons and multiple neutral delays in time derivative of states of the neurons. By making the use of a proper Lyapunov functional, we propose a novel sufficient time-independent stability criterion for this model of neutral-type neural networks. The proposed stability criterion in this paper can be absolutely expressed in terms of the parameters of the neural network model considered as this newly proposed criterion only relies on the relationships established among the network parameters. A numerical example is also given to indicate the advantages of the obtained stability criterion over the previously published stability results for the same class of Cohen-Grossberg neural networks. Since obtaining stability conditions for neutral-type Cohen-Grossberg neural networks with multiple delays is a difficult task to achieve, there are only few papers in the literature dealing with this problem. Therefore, the results given in the current paper makes an important contribution to the stability problem for this class of neutral-type neural networks.

中文翻译：

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具有多个时滞的中性型Cohen-Grossberg神经网络的进一步稳定性分析

本文的主要贡献在于研究中性型Cohen-Grossberg神经网络的稳定性分析，该神经网络在神经元状态具有多个时滞，在神经元状态的时间导数上具有多个中性延迟。通过使用适当的Lyapunov函数，我们为这种中立型神经网络模型提出了一种新颖的，与时间无关的充分稳定性准则。本文提出的稳定性准则可以用神经网络模型的参数来绝对表示，因为该新提出的准则仅依赖于网络参数之间建立的关系。还给出了一个数值示例，以表明所获得的稳定性标准相对于先前发布的针对同一类Cohen-Grossberg神经网络的稳定性结果的优势。由于要获得具有多个时滞的中立型Cohen-Grossberg神经网络的稳定性条件是一项艰巨的任务，因此，在文献中只有很少的论文涉及该问题。因此，本文给出的结果对此类中立型神经网络的稳定性问题做出了重要贡献。