Abstract This paper is concerned with a class of bidirectional associative memory (BAM) neural networks with discontinuous activations and time-varying delays. Under the basic framework of differential inclusions theory, the existence result of solutions in sense of Filippov solution is firstly established by using the fundamental solution matrix of coefficients and inequality analysis technique. Also, the boundness of the solutions can be estimated. Secondly, based on the non-smooth Lyapunov-like approach and by construsting suitable Lyapunov–Krasovskii functionals, some new sufficient criteria are given to ascertain the globally exponential stability of the anti-periodic solutions for the proposed neural network system. Furthermore, we have collated our effort with some previous existing ones in the literatures and showed that it can take more advantages. Finally, two examples with numerical simulations are exploited to illustrate the correctness.

中文翻译：

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时变时滞不连续双向联想记忆（BAM）神经网络反周期解的全局指数稳定性分析

摘要 本文涉及一类具有不连续激活和时变延迟的双向联想记忆 (BAM) 神经网络。在微分包含理论的基本框架下，利用系数的基本解矩阵和不等式分析技术，首先建立了Filippov解意义上的解的存在性结果。此外，可以估计解的边界。其次，基于非光滑类 Lyapunov 方法并通过构造合适的 Lyapunov-Krasovskii 泛函，给出了一些新的充分准则来确定所提出的神经网络系统的反周期解的全局指数稳定性。此外，我们已经将我们的努力与文献中的一些先前存在的努力进行了比较，并表明它可以发挥更多优势。最后，利用数值模拟的两个例子来说明正确性。