This research paper conducts an investigation into the stability issue for a more general class of neutral-type Hopfield neural networks that involves multiple time delays in the states of neurons and multiple neutral delays in the time derivatives of the states of neurons. By constructing a new proper Lyapunov functional, an alternative easily verifiable algebraic criterion for global asymptotic stability of this type of Hopfield neural systems is derived. This new stability condition is entirely independent of time and neutral delays. Two instructive examples are employed to indicate that the result obtained in this paper reveals a new set of sufficient stability criteria when it is compared with the previously reported stability results. Therefore, the proposed stability result enlarges the application domain of Hopfield neural systems of neutral types.

这篇研究论文对中性型Hopfield神经网络的更一般类别的稳定性问题进行了研究，该神经网络涉及神经元状态的多个时间延迟和神经元状态的时间导数的多个中性延迟。通过构造新的适当的Lyapunov泛函，得出了这种Hopfield神经系统的全局渐近稳定性的另一种易于验证的代数准则。这种新的稳定性条件完全不受时间和中性延迟的影响。使用两个说明性示例来表明，与先前报告的稳定性结果进行比较时，本文获得的结果揭示了一组新的足够的稳定性标准。因此，