This article investigates the general decay synchronization (GDS) for the bidirectional associative memory neural networks (BAMNNs). Compared with previous research results, both time-varying delays and distributed time delays are taken into consideration. By using Lyapunov method and using useful inequality techniques, some sufficient conditions on the GDS for BAMNNs are derived. Finally, a numerical example is also carried out to validate the practicability and feasibility of our proposed results. It is worth pointing out that the GDS may be specialized as exponential synchronization, polynomial synchronization and logarithmic synchronization. Besides, we can estimate the convergence rate of the synchronization by GDS. The obtained results in this article can be seen as the improvement and extension of the previously known works.

中文翻译：

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具有混合时滞的BAM神经网络的同步稳定性

本文研究了双向联想记忆神经网络（BAMNN）的通用衰减同步（GDS）。与以前的研究结果相比，时变时延和分布式时延都被考虑了。通过使用Lyapunov方法和有用的不等式技术，得出了GDS上BAMNN的一些充分条件。最后，还通过数值算例验证了我们提出的结果的实用性和可行性。值得指出的是，GDS可以专门化为指数同步，多项式同步和对数同步。此外，我们可以通过GDS估算同步的收敛速度。本文中获得的结果可以看作是对先前已知作品的改进和扩展。