This paper aims to discuss a class of discontinuous bidirectional associative memory (BAM) neural networks with discrete and distributed delays. By using the set-valued map, differential inclusions theory and fundamental solution matrix, the existence of almost-periodic solutions for the addressed neural network model is firstly discussed under some new conditions. Subsequently, based on the non-smooth analysis theory with Lyapunov-like strategy, the global exponential stability result of the almost-periodic solution for the proposed neural network system is also established without using any additional conditions. The results achieved in the paper extend some previous works on BAM neural networks to the discontinuous case and it is worth mentioning that it is the first time to investigate the almost-periodic dynamic behavior for the BAM neural networks like the form in this paper. Finally, in order to demonstrate the effectiveness of the theoretical schemes, simulation results of two topical numerical examples are delineated.

中文翻译：

---

具有离散和分布时滞的不连续双向联想记忆（BAM）神经网络的几乎周期解的稳定性分析

本文旨在讨论一类具有离散和分布式时延的不连续双向联想记忆（BAM）神经网络。通过使用集值映射，微分包含理论和基本解矩阵，首先在某些新条件下讨论了寻址神经网络模型的概周期解的存在性。随后，基于具有Lyapunov样策略的非光滑分析理论，在不使用任何其他条件的情况下，也建立了所提出的神经网络系统几乎周期解的全局指数稳定性结果。本文获得的结果将先前在BAM神经网络上的一些工作扩展到了不连续的情况，值得一提的是，这是第一次研究BAM神经网络的近似周期动态行为（如本文中的形式）。最后，为了证明理论方案的有效性，给出了两个局部数值例子的仿真结果。